The cost consequences of treatment-resistant depression.
ABSTRACT Treatment-resistant depression is a significant public health problem with profound effects on general medical and mental health-related health care costs.
To describe health care costs of patients with treatment-resistant depression as their illness progresses, in terms of pharmaceutical and medical expenditures, and to identify factors associated with increasing degrees of treatment resistance.
The MEDSTAT MarketScan Private Pay Fee for Service (FFS) Database, a medical and prescription claims database covering over 3.5 million enrollees, from 1995-2000. DESIGN AND STUDY SUBJECTS: 7737 patients with depression (ICD-9) who had 2 or more unsuccessful trials of antidepressant medication at an adequate dose for at least 4 weeks from 1995-2000 were defined as treatment-resistant in this study. Demographic and clinical characteristics were assessed for these patients with treatment-resistant depression. The number of changes in depression medication treatment regimens was used as a proxy for increasing degrees of treatment resistance and its severity. MAJOR OUTCOME MEASURE: Differences in health care expenditures associated with increasing degrees of treatment-resistant depression.
Total depression-related and general medical health care expenditures increased significantly as treatment-resistant depression increased in severity. Multivariate analyses of patient demographic characteristics were not associated with ongoing treatment resistance. Disease severity, type of antidepressant at index, comorbid mental health disorders, and membership in a managed health care plan were associated with increasing degrees of treatment resistance.
Depression and general medical health care expenditures increase with the degree of treatment-resistant depression. Disease management interventions for treatment-resistant depression that result in sustained remission early in the course of illness are most likely to be cost effective.
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ABSTRACT: Recent studies have shown overall accuracy rates of 72% and 88% using baseline and/or 1-week change in QEEG biomarkers to predict clinical outcome to treatment with various antidepressant medications. In some cases, findings have been replicated across academic institutions and have been studied in the context of randomized, placebo-controlled trials. Recent EEG findings are corroborated by studies that use techniques with greater spatial resolution (eg, PET, MEG) in localizing brain regions pertinent to clinical response. As such, EEG measurements increasingly are validated by other physiologic measurements that have the ability to assess deeper brain structures. Continued progress along these lines may lead to the realized promise of QEEG biomarkers as predictors of antidepressant treatment outcome in routine clinical practice. In the larger context, use of QEEG technology to predict antidepressant response in major depression may mean that more patients will achieve response and remission with less of the trial-and-error approach that currently accompanies antidepressant treatment.Psychiatric Clinics of North America 04/2007; 30(1):105-24. DOI:10.1016/j.psc.2006.12.002 · 2.13 Impact Factor
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ABSTRACT: RationaleLack of benefit from antidepressant drug therapy is a major source of human suffering, affecting at least 25% of people with major depressive disorder. We want to know whether nonresponse to antidepressants can be linked to aberrant neuroreceptor binding. ObjectiveThis study aims to assess the antidepressant binding in brain regions of depressed nonresponders compared with healthy controls. Materials and methodsHealthy volunteers and depressed subjects who had failed to benefit from at least 2 antidepressant treatments were recruited by newspaper advertisements. All subjects had received no antidepressant medication for at least 2months before positron emission tomography (PET) that was carried out with [11C]mirtazapine. Kinetic parameters of [11C]mirtazapine were determined from PET data in selected brain regions by the simplified reference tissue model. ResultsBinding potentials of [11C]mirtazapine in cerebral cortical regions were lower in depressed nonresponders than in healthy controls. Removal rates of [11C]mirtazapine were higher in diencephalic regions of depressed nonresponders than in healthy controls. ConclusionsPET neuroimaging with [11C]mirtazapine showed aberrant neuroreceptor binding in brain regions of depressed subjects who had failed to benefit from treatment with antidepressant drugs.Psychopharmacology 09/2009; 206(1):133-140. DOI:10.1007/s00213-009-1587-3 · 3.99 Impact Factor