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Am J Psychiatry. 2012 Nov;169(11):1185-93.

Treatment course with antidepressant therapy in late-life depression.

Author information

1
Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA. yvette@npg.wustl.edu

Abstract

OBJECTIVE:

In order to assess the effect of gray matter volumes and cortical thickness on antidepressant treatment response in late-life depression, the authors examined the relationship between brain regions identified a priori and Montgomery-Åsberg Depression Rating Scale (MADRS) scores over the course of an antidepressant treatment trial.

METHOD:

In a nonrandomized prospective trial, 168 patients who were at least 60 years of age and met DSM-IV criteria for major depression underwent MRI and were enrolled in a 12-week treatment study. Exclusion criteria included cognitive impairment or severe medical disorders. The volumes or cortical thicknesses of regions of interest that differed between the depressed group and a comparison group (N=50) were determined. These regions of interest were used in analyses of the depressed group to predict antidepressant treatment outcome. Mixed-model analyses adjusting for age, education, age at depression onset, race, baseline MADRS score, scanner, and interaction with time examined predictors of MADRS scores over time.

RESULTS:

Smaller hippocampal volumes predicted a slower response to treatment. With the inclusion of white matter hyper-intensity severity and neuropsychological factor scores, the best model included hippocampal volume and cognitive processing speed to predict rate of response over time. A secondary analysis showed that hippocampal volume and frontal pole thickness differed between patients who achieved remission and those who did not.

CONCLUSIONS:

These data expand our understanding of the prediction of treatment course in late-life depression. The authors propose that the primary variables of hippocampal volume and cognitive processing speed, subsuming other contributing variables (episodic memory, executive function, language processing) predict antidepressant response.

PMID:
23534057
PMCID:
PMC3752387
DOI:
10.1176/appi.ajp.2012.12010122
[Indexed for MEDLINE]
Free PMC Article
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