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P-1096 - Integration of Clinical, Psychosocial, Cognitive and Genetic Measures to Predict Antidepressant Treatment Outcome in mdd Patients: a Preliminary Clinical Study

Published online by Cambridge University Press:  15 April 2020

K. Lin
Affiliation:
Guangzhou Psychiatric Hospital, Guangzhou, China Psychiatriy, The First Affiliated Hospital of Jinan University, Guangzhou, China
G. Xu
Affiliation:
Guangzhou Psychiatric Hospital, Guangzhou, China Psychiatriy, The First Affiliated Hospital of Jinan University, Guangzhou, China
Y. Guo
Affiliation:
Guangzhou Psychiatric Hospital, Guangzhou, China Psychiatriy, The First Affiliated Hospital of Jinan University, Guangzhou, China
D. Rao
Affiliation:
Guangzhou Psychiatric Hospital, Guangzhou, China Psychiatriy, The First Affiliated Hospital of Jinan University, Guangzhou, China
H. Ouyang
Affiliation:
Guangzhou Psychiatric Hospital, Guangzhou, China Psychiatriy, The First Affiliated Hospital of Jinan University, Guangzhou, China
Y. Dang
Affiliation:
Guangzhou Psychiatric Hospital, Guangzhou, China Psychiatriy, The First Affiliated Hospital of Jinan University, Guangzhou, China
M. Zhang
Affiliation:
Guangzhou Psychiatric Hospital, Guangzhou, China Psychiatriy, The First Affiliated Hospital of Jinan University, Guangzhou, China
Y. Jia
Affiliation:
Guangzhou Psychiatric Hospital, Guangzhou, China Psychiatriy, The First Affiliated Hospital of Jinan University, Guangzhou, China
C. Ma
Affiliation:
Guangzhou Psychiatric Hospital, Guangzhou, China Psychiatriy, The First Affiliated Hospital of Jinan University, Guangzhou, China

Abstract

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Objectives

The main aim of this study is to investigate the capacity of a number of variables from four dimensions (clinical, psychosocial, cognitive and genetic domains) to predict the antidepressant treatment outcome, and combined the predictors in one integrate regression model with the aim to investigate which predictor contributed most.

Methods

In a semi-naturalistic prospective cohort study with a total of 241 fully assessed MDD patients, decrease in HAM-D scores from baseline to after 6 weeks of treatment was used to measure the antidepressant treatment outcome.

Results

The clinical and psychosocial model (R2 = 0.451) showed that HAM-D scores at baseline and MMPI-2 scale paranoia was the best clinical and psychosocial predictor of treatment outcome respectively. The cognitive model (R2 = 0.502) revealed that combination of better performance on TMT-B test and worse performance on TOH and WAIS-R Digit Backward testes could predict decline in HAM-D scores. The genetics analysis only found median of percent improvement in HAM-D scores in G-allele of GR gene BclI polymorphism carriers (72.2%) was significant lower than that in non-G allele carriers (80.1%). The integrate model showed that three predictors, combination of HAM-D scores at baseline, MMPI-2 scale paranoia and TMT-B test, explained 57.1% of the variance.

Conclusion

Three markers, HAM-D scores at baseline, MMPI-2 scale paranoia and TMT-B test, might serve as predictor of antidepressant outcome in daily psychiatric practice.

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Abstract
Copyright
Copyright © European Psychiatric Association 2012
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P-1096 - Integration of Clinical, Psychosocial, Cognitive and Genetic Measures to Predict Antidepressant Treatment Outcome in mdd Patients: a Preliminary Clinical Study
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