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Galkin S.A.
Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Science
Ivanova S.A.
Tomsk National Research Medical Center of the Russian Academy of Sciences
Bokhan N.A.
Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Science
Current methods for predicting therapeutic response in patients with depressive disorders
Journal: S.S. Korsakov Journal of Neurology and Psychiatry. 2022;122(2): 15‑21
Read: 1566 times
To cite this article:
Galkin SA, Ivanova SA, Bokhan NA. Current methods for predicting therapeutic response in patients with depressive disorders. S.S. Korsakov Journal of Neurology and Psychiatry.
2022;122(2):15‑21. (In Russ.)
https://doi.org/10.17116/jnevro202212202115
Depressive disorder is the most common mental illness, which is also one of the leading causes of disability worldwide. In addition, most suicides are associated with depression. Despite all modern achievements in the treatment of depressive disorders, up to 60% of patients did not adequately respond to psychopharmacotherapy (non—responders). Current guidelines and studies characterize non—responders as patients who have an inadequate response to taking two or more antidepressants from different classes within 4 weeks. However, in some cases, such a long wait for a therapeutic response can lead to adverse consequences. Thus, there is a need to develop prognostic methods of therapeutic resistance in patients with depressive disorders. The purpose of this review is to summarize current methods used to predict therapeutic response in patients with depressive disorders. A literature search was conducted using the search terms «depression», «antidepressant», «outcome», «predictor», «(bio) marker», «treatment—resistant depression» and «chronic depression». The search was conducted in the PubMed, Scopus, and Google Scholar databases for the time period from 2005 to 2020.
Authors:
Galkin S.A.
Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Science
Ivanova S.A.
Tomsk National Research Medical Center of the Russian Academy of Sciences
Bokhan N.A.
Mental Health Research Institute of the Tomsk National Research Medical Center of the Russian Academy of Science
Received:
16.09.2020
Accepted:
24.12.2020
List of references:
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