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Effectiveness of pharmacogenomics on the response and remission of treatment-resistant depression: a meta-analysis of randomised controlled trials

GENERAL PSYCHIATRY(2023)

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摘要
Background Pharmacogenomics (PGx) is a promising tool to realise tailored drug therapy for depression. Aims To investigate the treatment efficacy of PGx for treatment-resistant depression (TRD) compared with treatment as usual.Methods A systematic search was conducted in PubMed, Embase, the Cochrane Library, Web of Science and PsycINFO to identify relevant studies published from inception to 15 April 2023. Two arm randomised controlled trials (RCTs) exploring the efficacy of PGx-guided versus unguided treatment for TRD were included. The risk of bias in the included studies was evaluated using the Cochrane risk of bias assessment tool. The overall quality of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach.Results Seven RCTs (n=3003) comparing PGx-guided (n=1492) and unguided (n=1511) groups were identified and analysed. PGx-guided treatment was superior to treatment as usual in response (relative risk (RR)=1.31; 95% confidence interval (95% CI): 1.15 to 1.49; p<0.001) and remission (RR=1.40; 95% CI: 1.09 to 1.80; p=0.009) improvements. Effect sizes for acceptability (RR=0.90; 95% CI: 0.80 to 1.02; p=0.100) and side effect burden (RR=0.58; 95% CI: 0.29 to 1.15; p=0.120) between the two groups were not statistically different. The overall quality of evidence was rated from 'very low' (25%) to 'low' (75%) based on the GRADE criteria.Conclusions PGx-guided treatment has shown a small overall effect in improving the response and remission rates for patients with TRD. However, these results should be interpreted cautiously because of the few included studies and the low quality of evidence. Further high quality clinical trials are warranted to confirm the findings.PROSPERO registration number CRD42022340182.
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关键词
Depressive Disorder, Treatment-Resistant,Randomized Controlled Trials as Topic,Meta-Analysis as Topic
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