Title |
Antidepressant prescribing in the precision medicine era: a prescriber’s primer on pharmacogenetic tools
|
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Published in |
BMC Psychiatry, February 2017
|
DOI | 10.1186/s12888-017-1230-5 |
Pubmed ID | |
Authors |
Chad A. Bousman, Malcolm Forbes, Mahesh Jayaram, Harris Eyre, Charles F. Reynolds, Michael Berk, Malcolm Hopwood, Chee Ng |
Abstract |
About half of people who take antidepressants do not respond and many experience adverse effects. These detrimental outcomes are in part a result of the impact of an individual's genetic profile on pharmacokinetics and pharmcodynamics. If known and made available to clinicians, this could improve decision-making and antidepressant therapy outcomes. This has spurred the development of numerous pharmacogenetic-based decision support tools. In this article, we provide an overview of pharmacogenetic decision support tools, with particular focus on tools relevant to antidepressants. We briefly describe the evolution and current state of antidepressant pharmacogenetic decision support tools in clinical practice, followed by the evidence-base for their use. Finally, we present a series of considerations for clinicians contemplating use of these tools and discuss the future of antidepressant pharmacogenetic decision support tools. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | 31% |
Canada | 2 | 15% |
Australia | 2 | 15% |
United States | 1 | 8% |
Unknown | 4 | 31% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 54% |
Practitioners (doctors, other healthcare professionals) | 5 | 38% |
Scientists | 1 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 150 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 16% |
Student > Master | 23 | 15% |
Student > Ph. D. Student | 18 | 12% |
Other | 17 | 11% |
Student > Bachelor | 12 | 8% |
Other | 28 | 19% |
Unknown | 28 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 28 | 19% |
Pharmacology, Toxicology and Pharmaceutical Science | 24 | 16% |
Biochemistry, Genetics and Molecular Biology | 18 | 12% |
Neuroscience | 13 | 9% |
Psychology | 9 | 6% |
Other | 22 | 15% |
Unknown | 36 | 24% |