PMID- 35172174
OWN - NLM
STAT- MEDLINE
DCOM- 20220420
LR  - 20220420
IS  - 1573-2517 (Electronic)
IS  - 0165-0327 (Linking)
VI  - 304
DP  - 2022 May 1
TI  - Predictors of 4-week antidepressant outcome in patients with first-episode major 
      depressive disorder: An ROC curve analysis.
PG  - 59-65
LID - S0165-0327(22)00177-X [pii]
LID - 10.1016/j.jad.2022.02.029 [doi]
AB  - BACKGROUND: Pretreatment characteristics of patients, symptom and function could 
      be associated with antidepressant treatment outcome, but its predictive ability 
      is not adequate. Our study aimed to identify predictors of acute antidepressant 
      efficacy in patients with first-episode Major Depressive Disorder (MDD). METHODS: 
      187 patients with first-episode MDD were included and assessed clinical symptoms, 
      cognitive function and global functioning using the 17-item Hamilton Depression 
      Inventory (HAMD-17), MATRICS Consensus Cognitive Battery (MCCB) and Global 
      Assessment of Functioning (GAF). Participants received treatment with a SSRI 
      (escitalopram or venlafaxine) for 4 weeks. Logistic regression was used to 
      analyze the association between patients' characteristics, symptom profiles, 
      cognitive performance, and global functioning and the antidepressant outcome at 
      the end of 4 weeks, and ROC curve analysis was performed for predictive accuracy 
      with area under the receiver operating curve (AUC). RESULTS: Antidepressant 
      improvement, response and remission rate at week 4 was 87.7%, 64.7% and 42.8%, 
      respectively. The combination of pretreatment clinical profiles, speed of 
      processing and global functioning showed moderate discrimination of acute 
      improvement, response and remission with AUCs of 0.863, 0.812 and 0.734, 
      respectively. LIMITATIONS: The major limitation of the present study is the study 
      did not combine pharmacogenomics from the perspective of antidepressant drug 
      metabolism. CONCLUSION: Aside from the baseline clinical symptoms, cognitive 
      function and global functioning could be predictors of acute treatment outcome in 
      first episode MDD using escitalopram or venlafaxine. This relatively simple 
      application based on clinical symptoms and function seems to be cost-effective 
      method to identify individuals who are more likely to respond to antidepressant 
      treatment.
CI  - Copyright (c) 2022. Published by Elsevier B.V.
FAU - Zhou, Yanling
AU  - Zhou Y
AD  - Department of Psychiatry, Department of Neurology, Affiliated Brain Hospital, 
      Guangzhou Medical University, Guangzhou, China.
FAU - Zhang, Zhipei
AU  - Zhang Z
AD  - Department of Psychiatry, Department of Neurology, Affiliated Brain Hospital, 
      Guangzhou Medical University, Guangzhou, China; Southern Medical University, 
      Guangzhou, China.
FAU - Wang, ChengYu
AU  - Wang C
AD  - Department of Psychiatry, Department of Neurology, Affiliated Brain Hospital, 
      Guangzhou Medical University, Guangzhou, China.
FAU - Lan, Xiaofeng
AU  - Lan X
AD  - Department of Psychiatry, Department of Neurology, Affiliated Brain Hospital, 
      Guangzhou Medical University, Guangzhou, China.
FAU - Li, Weicheng
AU  - Li W
AD  - Department of Psychiatry, Department of Neurology, Affiliated Brain Hospital, 
      Guangzhou Medical University, Guangzhou, China; Southern Medical University, 
      Guangzhou, China.
FAU - Zhang, Muqin
AU  - Zhang M
AD  - Department of Psychiatry, Department of Neurology, Affiliated Brain Hospital, 
      Guangzhou Medical University, Guangzhou, China.
FAU - Lao, Guohui
AU  - Lao G
AD  - Department of Psychiatry, Department of Neurology, Affiliated Brain Hospital, 
      Guangzhou Medical University, Guangzhou, China.
FAU - Wu, Kai
AU  - Wu K
AD  - Department of Psychiatry, Department of Neurology, Affiliated Brain Hospital, 
      Guangzhou Medical University, Guangzhou, China; School of Biomedical Sciences and 
      Engineering, South china University of Technology, Guangzhou, China.
FAU - Chen, Jun
AU  - Chen J
AD  - Guangdong Institute of Medical Instruments, Guangzhou, China.
FAU - Li, Guixiang
AU  - Li G
AD  - Guangdong Institute of Medical Instruments, Guangzhou, China.
FAU - Ning, Yuping
AU  - Ning Y
AD  - Department of Psychiatry, Department of Neurology, Affiliated Brain Hospital, 
      Guangzhou Medical University, Guangzhou, China; Southern Medical University, 
      Guangzhou, China. Electronic address: ningjeny@126.com.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20220213
PL  - Netherlands
TA  - J Affect Disord
JT  - Journal of affective disorders
JID - 7906073
RN  - 0 (Antidepressive Agents)
RN  - 4O4S742ANY (Escitalopram)
RN  - 7D7RX5A8MO (Venlafaxine Hydrochloride)
SB  - IM
MH  - Antidepressive Agents/therapeutic use
MH  - *Depressive Disorder, Major/diagnosis/drug therapy/psychology
MH  - Escitalopram
MH  - Humans
MH  - ROC Curve
MH  - Treatment Outcome
MH  - Venlafaxine Hydrochloride/therapeutic use
OTO - NOTNLM
OT  - First-episode
OT  - Global functioning
OT  - Major depressive disorder
OT  - Predictor
OT  - Speed of processing
EDAT- 2022/02/17 06:00
MHDA- 2022/04/21 06:00
CRDT- 2022/02/16 20:07
PHST- 2021/05/12 00:00 [received]
PHST- 2022/02/06 00:00 [revised]
PHST- 2022/02/12 00:00 [accepted]
PHST- 2022/02/17 06:00 [pubmed]
PHST- 2022/04/21 06:00 [medline]
PHST- 2022/02/16 20:07 [entrez]
AID - S0165-0327(22)00177-X [pii]
AID - 10.1016/j.jad.2022.02.029 [doi]
PST - ppublish
SO  - J Affect Disord. 2022 May 1;304:59-65. doi: 10.1016/j.jad.2022.02.029. Epub 2022 
      Feb 13.