Literature DB >> 24926841

Predictors of antidepressant response: A selective review.

Seetal Dodd1, Michael Berk.   

Abstract

Modern antidepressant drugs have response rates in the 65% range. Considerable effort has been made to predict which patients would be more likely to respond to antidepressant treatment. Some progress has been made, more in finding psychological predictors than biological predictors of antidepressant response. In spite of slow progress, these findings have made a valuable contribution towards the understanding of antidepressant response. In future it may be possible for psychiatrists to use a more broad-based approach, tailoring therapies to the clinical profile of individuals.

Entities:  

Keywords:  antidepressant; depression; predictor; response

Year:  2004        PMID: 24926841     DOI: 10.1080/13651500410005423

Source DB:  PubMed          Journal:  Int J Psychiatry Clin Pract        ISSN: 1365-1501            Impact factor:   1.812


  6 in total

Review 1.  Ketamine for depression: where do we go from here?

Authors:  Marije Aan Het Rot; Carlos A Zarate; Dennis S Charney; Sanjay J Mathew
Journal:  Biol Psychiatry       Date:  2012-06-16       Impact factor: 13.382

Review 2.  Stage managing bipolar disorder.

Authors:  Michael Berk; Lesley Berk; Seetal Dodd; Sue Cotton; Craig Macneil; Rothanthi Daglas; Philippe Conus; Andreas Bechdolf; Steven Moylan; Gin S Malhi
Journal:  Bipolar Disord       Date:  2013-06-20       Impact factor: 6.744

3.  Concordance between actual and pharmacogenetic predicted desvenlafaxine dose needed to achieve remission in major depressive disorder: a 10-week open-label study.

Authors:  Chad A Bousman; Daniel J Müller; Chee H Ng; Keith Byron; Michael Berk; Ajeet B Singh
Journal:  Pharmacogenet Genomics       Date:  2017-01       Impact factor: 2.089

Review 4.  Antidepressant prescribing in the precision medicine era: a prescriber's primer on pharmacogenetic tools.

Authors:  Chad A Bousman; Malcolm Forbes; Mahesh Jayaram; Harris Eyre; Charles F Reynolds; Michael Berk; Malcolm Hopwood; Chee Ng
Journal:  BMC Psychiatry       Date:  2017-02-08       Impact factor: 3.630

5.  Effects of persisting emotional impact from child abuse and norepinephrine transporter genetic variation on antidepressant efficacy in major depression: a pilot study.

Authors:  Ajeet Bhagat Singh; Chad A Bousman; Chee Hong Ng; Keith Byron; Michael Berk
Journal:  Clin Psychopharmacol Neurosci       Date:  2015-04-30       Impact factor: 2.582

6.  Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder.

Authors:  Azmeraw T Amare; Klaus Oliver Schubert; Fasil Tekola-Ayele; Yi-Hsiang Hsu; Katrin Sangkuhl; Gregory Jenkins; Ryan M Whaley; Poulami Barman; Anthony Batzler; Russ B Altman; Volker Arolt; Jürgen Brockmöller; Chia-Hui Chen; Katharina Domschke; Daniel K Hall-Flavin; Chen-Jee Hong; Ari Illi; Yuan Ji; Olli Kampman; Toshihiko Kinoshita; Esa Leinonen; Ying-Jay Liou; Taisei Mushiroda; Shinpei Nonen; Michelle K Skime; Liewei Wang; Masaki Kato; Yu-Li Liu; Verayuth Praphanphoj; Julia C Stingl; William V Bobo; Shih-Jen Tsai; Michiaki Kubo; Teri E Klein; Richard M Weinshilboum; Joanna M Biernacka; Bernhard T Baune
Journal:  Front Psychiatry       Date:  2018-03-06       Impact factor: 4.157

  6 in total

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