Publications [#277070] of Kathleen A. Welsh-Bohmer

Journal Articles

1. Sheline, YI; Disabato, BM; Hranilovich, J; Morris, C; D'Angelo, G; Pieper, C; Toffanin, T; Taylor, WD; MacFall, JR; Wilkins, C; Barch, DM; Welsh-Bohmer, KA; Steffens, DC; Krishnan, RR; Doraiswamy, PM (2012). Treatment course with antidepressant therapy in late-life depression.. Am J Psychiatry, 169(11), 1185-1193. [23034601], [doi]
   (last updated on 2024/04/24)

   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.