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Does Pharmacogenomic Testing Improve Clinical Outcomes for Major Depressive Disorder? A Systematic Review of Clinical Trials and Cost-Effectiveness Studies

J Clin Psychiatry 2017;78(6):720–729
10.4088/JCP.15r10583

Objective: Pharmacogenomic testing has become scalable and available to the general public. Pharmacogenomics has shown promise for predicting antidepressant response and tolerability in the treatment of major depressive disorder (MDD). In theory, pharmacogenomics can improve clinical outcomes by guiding antidepressant selection and dosing. The current systematic review examines the extant literature to determine the impact of pharmacogenomic testing on clinical outcomes in MDD and assesses its cost-effectiveness.

Data Sources: The MEDLINE/PubMed and Google Scholar databases were systematically searched for relevant articles published prior to October 2015. Search terms included various combinations of the following: major depressive disorder (MDD), depression, mental illness, mood disorder, antidepressant, response, remission, outcome, pharmacogenetic, pharmacogenomics, pharmacodynamics, pharmacokinetic, genetic testing, genome wide association study (GWAS), CYP450, personalized medicine, cost-effectiveness, and pharmacoeconomics.

Study Selection: Of the 66 records identified from the initial search, relevant clinical studies, written in English, assessing the cost-effectiveness and/or efficacy of pharmacogenomic testing for MDD were included.

Data Extraction: Each publication was critically examined for relevant data.

Results: Two nonrandomized, open-label, 8-week, prospective studies reported overall greater improvement in depressive symptom severity in the group of MDD subjects receiving psychiatric care guided by results of combinatorial pharmacogenomic testing (GeneSight) when compared to the unguided group. One industry-sponsored, randomized, double-blind, 10-week prospective study reported a trend for improved outcomes for the GeneSight-guided group; however, the trend did not reach statistical significance. Another industry-sponsored, randomized, double-blind, 12-week prospective study reported a 2.5-fold increase in remission rates in the CNSDose-guided group (P < .0001). One naturalistic, unblinded, industry-sponsored study showed clinical improvement when pharmacogenomics testing guided prescribing; however, this study lacked a control group. A single cost-effectiveness study concluded that single gene testing was not cost-effective. Conversely, a separate study reported that combinatorial pharmacogenomic testing is cost-effective.

Conclusions: A limited number of studies have shown promise for the clinical utility of pharmacogenomic testing; however, cost-effectiveness of pharmacogenomics, as well as demonstration of improved health outcomes, is not yet supported with replicated evidence.