Econstudentlog

Prevention of Late-Life Depression (II)

Some more observations from the book:

In contrast to depression in childhood and youth when genetic and developmental vulnerabilities play a significant role in the development of depression, the development of late-life depression is largely attributed to its interactions with acquired factors, especially medical illness [17, 18]. An analysis of the WHO World Health Survey indicated that the prevalence of depression among medical patients ranged from 9.3 to 23.0 %, significantly higher than that in individuals without medical conditions [19]. Wells et al. [20] found in the Epidemiologic Catchment Area Study that the risk of developing lifetime psychiatric disorders among individuals with at least one medical condition was 27.9 % higher than among those without medical conditions. […] Depression and disability mutually reinforce the risk of each other, and adversely affect disease progression and prognosis [21, 25]. […] disability caused by medical conditions serves as a risk factor for depression [26]. When people lose their normal sensory, motor, cognitive, social, or executive functions, especially in a short period of time, they can become very frustrated or depressed. Inability to perform daily tasks as before decreases self-esteem, reduces independence, increases the level of psychological stress, and creates a sense of hopelessness. On the other hand, depression increases the risk for disability. Negative interpretation, attention bias, and learned hopelessness of depressed persons may increase risky health behaviors that exacerbate physical disorders or disability. Meanwhile, depression-related cognitive impairment also affects role performance and leads to functional disability [25]. For example, Egede [27] found in the 1999 National Health Interview Survey that the risk of having functional disability among patients with the comorbidity of diabetes and depression were approximately 2.5–5 times higher than those with either depression or diabetes alone. […]  A leading cause of disability among medical patients is pain and pain-related fears […] Although a large proportion of pain complaints can be attributed to physiological changes from physical disorders, psychological factors (e.g., attention, interpretation, and coping skills) play an important role in perception of pain […] Bair et al. [31] indicated in a literature review that the prevalence of pain was higher among depressed patients than non-depressed patients, and the prevalence of major depression was also higher among pain patients comparing to those without pain complaints.”

Alcohol use has more serious adverse health effects on older adults than other age groups, since aging-related physiological changes (e.g. reduced liver detoxification and renal clearance) affect alcohol metabolism, increase the blood concentration of alcohol, and magnify negative consequences. More importantly, alcohol interacts with a variety of frequently prescribed medications potentially influencing both treatment and adverse effects. […] Due to age-related changes in pharmacokinetics and pharmacodynamics, older adults are a vulnerable population to […] adverse drug effects. […] Adverse drug events are frequently due to failure to adjust dosage or to account for drug–drug interactions in older adults [64]. […] Loneliness […] is considered as an independent risk factor for depression [46, 47], and has been demonstrated to be associated with low physical activity, increased cardiovascular risks, hyperactivity of the hypothalamic-pituitary-adrenal axis, and activation of immune response [for details, see Cacioppo & Patrick’s book on these topics – US] […] Hopelessness is a key concept of major depression [54], and also an independent risk factor of suicidal ideation […] Hopelessness reduces expectations for the future, and negatively affects judgment for making medical and behavioral decisions, including non-adherence to medical regimens or engaging in unhealthy behaviors.”

Co-occurring depression and medical conditions are associated with more functional impairment and mortality than expected from the severity of the medical condition alone. For example, depression accompanying diabetes confers increased functional impairment [27], complications of diabetes [65, 66], and mortality [6771]. Frasure-Smith and colleagues highlighted the prognostic importance of depression among persons who had sustained a myocardial infarction (MI), finding that depression was a significant predictor of mortality at both 6 and 18 months post MI [72, 73]. Subsequent follow-up studies have borne out the increased risk conferred by depression on the mortality of patients with cardiovascular disease [10, 74, 75]. Over the course of a 2-year follow-up interval, depression contributed as much to mortality as did myocardial infarction or diabetes, with the population attributable fraction of mortality due to depression approximately 13 % (similar to the attributable risk associated with heart attack at 11 % and diabetes at 9 %) [76]. […] Although the bidirectional relationship between physical disorders and depression has been well known, there are still relatively few randomized controlled trials on preventing depression among medically ill patients. […] Rates of attrition [in post-stroke depression prevention trials has been observed to be] high […] Stroke, acute coronary syndrome, cancer, and other conditions impose a variety of treatment burdens on patients so that additional interventions without direct or immediate clinical effects may not be acceptable [95]. So even with good participation rates, lack of adherence to the intervention might limit effects.”

Late-life depression (LLD) is a heterogeneous disease, with multiple risk factors, etiologies, and clinical features. It has been recognized for many years that there is a significant relationship between the presence of depression and cerebrovascular disease in older adults [1, 2]. This subtype of LLD was eventually termed “vascular depression.” […] There have been a multitude of studies associating white matter abnormalities with depression in older adults using MRI technology to visualize lesions, or what appear as hyperintensities in the white matter on T2-weighted scans. A systematic review concluded that white matter hyperintensities (WMH) are more common and severe among older adults with depression compared to their non-depressed peers [9]. […] WMHs are associated with older age [13] and cerebrovascular risk factors, including diabetes, heart disease, and hypertension [14–17]. White matter severity and extent of WMH volume has been related to the severity of depression in late life [18, 19]. For example, among 639 older, community-dwelling adults, white matter lesion (WML) severity was found to predict depressive episodes and symptoms over a 3-year period [19]. […] Another way of investigating white matter integrity is with diffusion tensor imaging (DTI), which measures the diffusion of water in tissues and allows for indirect evidence of the microstructure of white matter, most commonly represented as fractional anisotropy (FA) and mean diffusivity (MD). DTI may be more sensitive to white matter pathology than is quantification of WMH […] A number of studies have found lower FA in widespread regions among individuals with LLD relative to controls [34, 36, 37]. […] lower FA has been associated with poorer performance on measures of cognitive functioning among patients with LLD [35, 38–40] and with measures of cerebrovascular risk severity. […] It is important to recognize that FA reflects the organization of fiber tracts, including fiber density, axonal diameter, or myelination in white matter. Thus, lower FA can result from multiple pathophysiological sources [42, 43]. […] Together, the aforementioned studies provide support for the vascular depression hypothesis. They demonstrate that white matter integrity is reduced in patients with LLD relative to controls, is somewhat specific to regions important for cognitive and emotional functioning, and is associated with cognitive functioning and depression severity. […] There is now a wealth of evidence to support the association between vascular pathology and depression in older age. While the etiology of depression in older age is multifactorial, from the epidemiological, neuroimaging, behavioral, and genetic evidence available, we can conclude that vascular depression represents one important subtype of LLD. The mechanisms underlying the relationship between vascular pathology and depression are likely multifactorial, and may include disrupted connections between key neural regions, reduced perfusion of blood to key brain regions integral to affective and cognitive processing, and inflammatory processes.”

Cognitive changes associated with depression have been the focus of research for decades. Results have been inconsistent, likely as a result of methodological differences in how depression is diagnosed and cognitive functioning measured, as well as the effects of potential subtypes and the severity of depression […], though deficits in executive functioning, learning and memory, and attention have been associated with depression in most studies [75]. In older adults, additional confounding factors include the potential presence of primary degenerative disorders, such as Alzheimer’s disease, which can pose a challenge to differential diagnosis in its early stages. […] LLD with cognitive dysfunction has been shown to result in greater disability than depressive symptoms alone [6], and MCI [mild cognitive impairment, US] with co-occurring LLD has been shown to double the risk of developing Alzheimer’s disease (AD) compared to MCI alone [86]. The conversion from MCI to AD also appears to occur earlier in patients with cooccurring depressive symptoms, as demonstrated by Modrego & Ferrandez [86] in their prospective cohort study of 114 outpatients diagnosed with amnestic MCI. […] Given accruing evidence for abnormal functioning of a number of cortical and subcortical networks in geriatric depression, of particular interest is whether these abnormalities are a reflection of the actively depressed state, or whether they may persist following successful resolution of symptoms. To date, studies have investigated this question through either longitudinal investigation of adults with geriatric depression, or comparison of depressed elders who are actively depressed versus those who have achieved symptom remission. Of encouragement, successful treatment has been reliably associated with normalization of some aspects of disrupted network functioning. For example, successful antidepressant treatment is associated with reduction of the elevated cerebral glucose metabolism observed during depressed states (e.g., [71–74]), with greater symptom reduction associated with greater metabolic change […] Taken together, these studies suggest that although a subset of the functional abnormalities observed during the LLD state may resolve with successful treatment, other abnormalities persist and may be tied to damage to the structural connectivity in important affective and cognitive networks. […] studies suggest a chronic decrement in cognitive functioning associated with LLD that is not adequately addressed through improvement of depressive symptoms alone.”

A review of the literature on evidence-based treatments for LLD found that about 50 % of patients improved on antidepressants, but that the number needed to treat (NNT) was quite high (NNT = 8, [139]) and placebo effects were significant [140]. Additionally, no difference was demonstrated in the effectiveness of one antidepressant drug class over another […], and in one-third of patients, depression was resistant to monotherapy [140]. The addition of medications or switching within or between drug classes appears to result in improved treatment response for these patients [140, 141]. A meta-analysis of patient-level variables demonstrated that duration of depressive symptoms and baseline depression severity significantly predicts response to antidepressant treatment in LLD, with chronically depressed older patients with moderate-to-severe symptoms at baseline experiencing more improvement in symptoms than mildly and acutely depressed patients [142]. Pharmacological treatment response appears to range from incomplete to poor in LLD with co-occurring cognitive impairment.”

“[C]ompared to other formulations of prevention, such as primary, secondary, or tertiary — in which interventions are targeted at the level of disease/stage of disease — the IOM conceptual framework involves interventions that are targeted at the level of risk in the population [2]. […] [S]elective prevention studies have an important “numbers” advantage — similar to that of indicated prevention trials: the relatively high incidence of depression among persons with key risk markers enables investigator to test interventions with strong statistical power, even with somewhat modest sample sizes. This fact was illustrated by Schoevers and colleagues [3], in which the authors were able to account for nearly 50 % of total risk of late-life depression with consideration of only a handful of factors. Indeed, research, largely generated by groups in the Netherlands and the USA, has identified that selective prevention may be one of the most efficient approaches to late-life depression prevention, as they have estimated that targeting persons at high risk for depression — based on risk markers such as medical comorbidity, low social support, or physical/functional disability — can yield theoretical numbers needed to treat (NNTs) of approximately 5–7 in primary care settings [4–7]. […] compared to the findings from selective prevention trials targeting older persons with general health/medical problems, […] trials targeting older persons based on sociodemographic risk factors have been more mixed and did not reveal as consistent a pattern of benefits for selective prevention of depression.”

Few of the studies in the existing literature that involve interventions to prevent depression and/or reduce depressive symptoms in older populations have included economic evaluations [13]. The identification of cost-effective interventions to provide to groups at high risk for depression is an important public health goal, as such treatments may avert or reduce a significant amount of the disease burden. […] A study by Katon and colleagues [8] showed that elderly patients with either subsyndromal or major depression had significantly higher medical costs during the previous 6 months than those without depression; total healthcare costs were $1,045 to $1,700 greater, and total outpatient/ambulatory costs ranged from being $763 to $979 more, on average. Depressed patients had greater usage of health resources in every category of care examined, including those that are not mental health-related, such as emergency department visits. No difference in excess costs was found between patients with a DSM-IV depressive disorder and those with depressive symptoms only, however, as mean total costs were 51 % higher in the subthreshold depression group (95 % CI = 1.39–1.66) and 49 % higher in the MDD/dysthymia group (95 % CI = 1.28–1.72) than in the nondepressed group [8]. In a similar study, the usage of various types of health services by primary care patients in the Netherlands was assessed, and average costs were determined to be 1,403 more in depressed individuals versus control patients [21]. Study investigators once again observed that patients with depression had greater utilization of both non-mental and mental healthcare services than controls.”

“In order for routine depression screening in the elderly to be cost-effective […] appropriate follow-up measures must be taken with those who screen positive, including a diagnostic interview and/or referral to a mental health professional [this – the necessity/requirement of proper follow-up following screens in order for screening to be cost-effective – is incidentally a standard result in screening contexts, see also Juth & Munthe’s book – US] [23, 25]. For example, subsequent steps may include initiation of psychotherapy or antidepressant treatment. Thus, one reason that the USPSTF does not recommend screening for depression in settings where proper mental health resources do not exist is that the evidence suggests that outcomes are unlikely to improve without effective follow-up care […]  as per the USPSTF suggestion, Medicare will only cover the screening when the appropriate supports for proper diagnosis and treatment are available […] In order to determine which interventions to prevent and treat depression should be provided to those who screen positive for depressive symptoms and to high-risk populations in general, cost-effectiveness analyses must be completed for a variety of different treatments and preventive measures. […] questions remain regarding whether annual versus other intervals of screening are most cost-effective. With respect to preventive interventions, the evidence to date suggests that these are cost-effective in settings where those at the highest risk are targeted.”

February 19, 2018 - Posted by | Books, Cardiology, Diabetes, Health Economics, Neurology, Pharmacology, Psychiatry, Psychology

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