Literature DB >> 23886402

Trajectories of individual symptoms in remitters versus non-remitters with depression.

Hitoshi Sakurai1, Hiroyuki Uchida, Takayuki Abe, Shinichiro Nakajima, Takefumi Suzuki, Bruce G Pollock, Yuji Sato, Masaru Mimura.   

Abstract

BACKGROUND: It remains unclear regarding the contribution of each individual symptom in predicting the outcome in major depressive disorder (MDD). The objective of this analysis was to evaluate trajectories of individual symptoms over time to identify which specific depressive item(s) could predict subsequent clinical response.
METHODS: The data of 2874 outpatients with nonpsychotic MDD who received citalopram for up to 14 weeks in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial were analyzed. Average trajectories of individual symptoms over time were estimated for remitters and non-remitters. Moreover, specific symptoms whose improvement at week 2 predicted remission were identified, using binary logistic regression analysis.
RESULTS: Trajectories were significantly different between remitters and non-remitters in all depressive symptoms. All depressive symptoms in the 16-item Quick Inventory of Depressive Symptomatology, Self-Report (QIDS-SR16) in the two groups, except for hypersomnia and weight change in non-remitters, substantially improved within 2 weeks and gradually continued to improve thereafter throughout the 14 weeks. Early improvements in the following five symptoms, in order of magnitude, in the QIDS-SR16 were significantly associated with remission: sad mood, negative self-view, feeling slowed down, low energy, and restlessness (P<0.001, P<0.001, P=0.001, P=0.004, P=0.021). LIMITATIONS: The participants were limited to the nonpsychotic MDD outpatients who received citalopram. Further, symptomatology was not evaluated at the very beginning of treatment.
CONCLUSIONS: While the data pertain to citalopram and replication is necessary for other antidepressants, early improvements in certain core depressive symptoms may serve as a predictor of subsequent remission.
© 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Depression; Major depressive disorder; Prediction; Remission

Mesh:

Substances:

Year:  2013        PMID: 23886402     DOI: 10.1016/j.jad.2013.06.035

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  13 in total

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Authors:  Hitoshi Sakurai; Takefumi Suzuki; Kimio Yoshimura; Masaru Mimura; Hiroyuki Uchida
Journal:  Psychopharmacology (Berl)       Date:  2017-05-03       Impact factor: 4.530

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6.  Prediction of short-term antidepressant response using probabilistic graphical models with replication across multiple drugs and treatment settings.

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7.  Does early improvement in depressive symptoms predict subsequent remission in patients with depression who are treated with duloxetine?

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Authors:  Juliana J Petersen; Johannes Hartig; Michael A Paulitsch; Manuel Pagitz; Karola Mergenthal; Sandra Rauck; Andreas Reif; Ferdinand M Gerlach; Jochen Gensichen
Journal:  PLoS One       Date:  2018-09-07       Impact factor: 3.240

9.  Divergent topological architecture of the default mode network as a pretreatment predictor of early antidepressant response in major depressive disorder.

Authors:  Zhenghua Hou; Zan Wang; Wenhao Jiang; Yingying Yin; Yingying Yue; Yuqun Zhang; Xiaopeng Song; Yonggui Yuan
Journal:  Sci Rep       Date:  2016-12-14       Impact factor: 4.379

10.  Severity, course trajectory, and within-person variability of individual symptoms in patients with major depressive disorder.

Authors:  W A van Eeden; A M van Hemert; I V E Carlier; B W Penninx; E J Giltay
Journal:  Acta Psychiatr Scand       Date:  2018-12-09       Impact factor: 6.392

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