Taylor RW, Marwood L, Greer B, Strawbridge R, Cleare AJ. Predictors of response to augmentation treatment in patients with treatment-resistant depression: A systematic review.
J Psychopharmacol 2019;
33:1323-1339. [PMID:
31526204 DOI:
10.1177/0269881119872194]
[Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND
Treatment-resistant depression is an important contributor to the global burden of depression. Antidepressant augmentation is a recommended treatment strategy for treatment-resistant patients, but outcomes remain poor. Identifying factors that are predictive of response to augmentation treatments may improve outcomes.
AIMS
This review aimed to synthesise the existing literature examining predictors of response to augmentation treatments in patients who had insufficiently responded to initial treatment.
METHODS
A systematic search was conducted identifying 2241 unique manuscripts. 24 examining predictors of outcome to pharmacological or psychological augmentation treatment were included in this review.
RESULTS
Atypical antipsychotics were the most frequently assessed treatment class (nine studies), closely followed by mood stabilisers (eight studies). Only one eligible psychological augmentation study was identified. Early response to treatment (week 2) was the best-supported predictor of subsequent treatment outcome, reported by six studies. Many predictor variables were only assessed by one report and others such as pre-treatment severity yielded contradictory results, both within and across treatment classes.
CONCLUSIONS
This review highlights the importance of early response as a predictor of pharmacological augmentation outcome, with implications for both the monitoring and treatment of resistant unipolar patients. Further replication is needed across specific interventions to fully assess the generalisability of this finding. However, the clear lack of consistent evidence for other predictive factors both within and across treatments, and the scarce examination of psychological augmentation, demonstrates the need for much more research of a high quality if response prediction is to improve outcomes for patients with treatment-resistant depression.
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