Impact of Prior Treatment Exposure on Response to Antidepressant Treatment in Late Life

Tew, James D.; Mulsant, Benoit H.; Houck, Patricia R.; Lenze, Eric J.; Whyte, Ellen M.; Miller, Mark D.; Stack, Jacqueline A.; Bensasi, Salem; Reynolds, Charles F.

doi:10.1097/01.jgp.0000222311.70424.85

Cited by 26 publications

(19 citation statements)

References 38 publications

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“…The group of predictors of treatment response identified by our univariate logistic regression is congruent with the previous literature reporting on the contribution of several demographic and clinical factors in predicting treatment response in late-life major depression (7,(9)(10)(11). Using signal detection theory, we identified the hierarchy of predictors of treatment response in two decision tree models.…”

Section: Discussionsupporting

confidence: 73%

“…During the acute phase of treatment in maintenance therapies in late-life depression 2, the subjects were treated openly with paroxetine in doses adjusted between 10 and 40 mg/day based on tolerability and response (mean [SD] final dose: 26 [11] mg/day), combined with weekly interpersonal therapy. In the double-blind randomized comparison of nortriptyline and paroxetine in late-life depression, the subjects were randomly assigned to blinded treatment with nortriptyline or paroxetine.…”

Section: Acute Treatment Protocolsmentioning

confidence: 99%

“…Furthermore, we have identified several biological, clinical, and psychosocial characteristics as predictors of treatment response in latelife major depression: allelic variation in the serotonin transporter promoter, REM sleep latency, cerebral glucose metabolism, age at onset of first episode, sleep disturbances at baseline, baseline Hamilton Depression Rating Scale (HAM-D) scores, baseline anxiety levels, suicidal ideation, response and adherence to previous antidepressant treatment, family support, and social inequalities (7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17). To our knowledge, there is no published report of a treatment decision tree based on a hierarchy of factors integrating various predictors of response in acute treatment of late-life major depression.…”

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confidence: 99%

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Empirically Derived Decision Trees for the Treatment of Late-Life Depression

Andreescu

Mulsant²,

Houck³

et al. 2008

AJP

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Objective-Several predictors of treatment response in late-life depression have been reported in the literature. The aim of this analysis was to develop a clinically useful algorithm that would allow clinicians to predict which patients will likely respond to treatment and thereby guide clinical decision making.Method-A total of 461 patients with late-life depression were treated under structured conditions for up to 12 weeks and assessed weekly with the 17-item Hamilton Rating Scale for Depression . The authors developed a hierarchy of predictors of treatment response using signaldetection theory. The authors developed two models, one minimizing false predictions of future response and one minimizing false predictions of future nonresponse, to offer clinicians two clinically useful treatment algorithms.Results-In the first model, early symptom improvement (defined by the relative change in HAM-D-17 total score from baseline to week 4), lower baseline anxiety, and an older age of onset predict response at 12 weeks. In the second model, early symptom improvement represents the principal guide in tailoring treatment, followed by baseline anxiety level, baseline sleep disturbance, and-for a minority of patients-the adequacy of previous antidepressant treatment.Conclusions-Our two models, developed to help clinicians in different clinical circumstances, illustrate the possibility of tailoring the treatment of late-life depression based on clinical characteristics and confirm the importance of early observed changes in clinical status.Late-life major depression is associated with emotional suffering, disability, caregiver strain, suicide, and poor compliance with other medical treatments (1). Successful antidepressant treatment is one of the most effective ways to reduce disability, prevent morbidity, and improve quality of life in an older depressed patient (2,3). In many cases, patients appear to be resistant to treatment because their antidepressants are switched prematurely (4,5). If treating clinicians knew the probability of treatment response earlier in the course of treatment, they would be in a better position to advise patients about various treatment options. These options could include continuing the current medication, augmenting current pharmacotherapy, or switching to another approach (6,7). Previously, our group has shown that a patient's clinical status after 4 weeks of treatment predicts reliably their response status at week 12 (6). Furthermore, we have identified several biological, clinical, and psychosocial characteristics as predictors of treatment response in latelife major depression: allelic variation in the serotonin transporter promoter, REM sleep latency, cerebral glucose metabolism, age at onset of first episode, sleep disturbances at baseline, baseline Hamilton Depression Rating Scale (HAM-D) scores, baseline anxiety levels, suicidal ideation, response and adherence to previous antidepressant treatment, family support, and social inequalities (7-17). To our knowledge, there is n...

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Section: Discussionsupporting

confidence: 73%

Section: Acute Treatment Protocolsmentioning

confidence: 99%

mentioning

confidence: 99%

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Empirically Derived Decision Trees for the Treatment of Late-Life Depression

Andreescu

Mulsant²,

Houck³

et al. 2008

AJP

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“…meeting criteria for MDD and MADRS≥17) despite an adequate antidepressant trial of at least 4 weeks, i.e. CAD score of 3 or 4 [40] . Patient and caregiver’s treatment satisfaction was assessed with the 3-item Client Satisfaction Questionnaire [41] at 4, 8, and 12 weeks (eTable 2).…”

Section: Methodsmentioning

confidence: 99%

Problem Adaptation Therapy for Older Adults With Major Depression and Cognitive Impairment

et al. 2015

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“…Further, the elderly are more likely to experience relapses and recurrences than younger adults [11–13]. The failure of first-line treatment to induce remission in patients leads to impaired psychosocial function and diminished quality of life [14–16].…”

Section: Introductionmentioning

confidence: 99%

A Review of Brain Stimulation Treatments for Late-Life Depression

Blumberger

Hsu

Daskalakis

2015

Curr Treat Options Psych

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Opinion Statement Recurrence, relapse and resistance to first-line therapies are common and pervasive issues in the treatment of depression in older adults. As a result, brain stimulation modalities are essential treatment options in this population. The majority of data for the effectiveness of brain stimulation modalities comes from electroconvulsive therapy (ECT) studies. Current ECT trials are focused on prolonging response after a successful course and mitigating the cognitive adverse effects. Newer forms of brain stimulation have emerged; unfortunately, as with most advances in medicine older adults have not been systematically included in clinical trials. Repetitive transcranial magnetic stimulation has demonstrated efficacy in younger adults and there is emerging data to support its use in late-life depression (LLD). It will be imperative that older adults be included in future transcranial direct current stimulation and magnetic seizure therapy clinical trials. Unclear efficacy results are a concern for both vagus nerve stimulation and deep brain stimulation.

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Impact of Prior Treatment Exposure on Response to Antidepressant Treatment in Late Life

Cited by 26 publications

References 38 publications

Empirically Derived Decision Trees for the Treatment of Late-Life Depression

Empirically Derived Decision Trees for the Treatment of Late-Life Depression

Problem Adaptation Therapy for Older Adults With Major Depression and Cognitive Impairment

A Review of Brain Stimulation Treatments for Late-Life Depression

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