Major depressive disorder, also called depression or clinical depression, is one of the most common mental disorders in the United States. It affects approximately 17.3 million American adults in a given year, with many individuals facing a long and challenging trial-and-error process to find the right antidepressant [1].
One of the greatest challenges of depression treatment is the wide variability in outcomes and side effects among patients treated with antidepressants. When prescribing, healthcare providers consider variables such as a patient’s age, gender, symptom profile, and potentially interacting medications. However, with genetic variants contributing to nearly 50% of antidepressant response rates, there is a huge opportunity to leverage pharmacogenomic (PGx) testing to optimize prescriptions [2].
Here’s how PGx testing can help improve patient outcomes for greater patient satisfaction and treatment adherence.
Choosing a depression medication
In 2020, an estimated 66.0%. American adults aged 18 or older with major depressive episodes received treatment in the past year [3]. Research shows that as few as one in four individuals with depression reach full remission after a first medication trial [4]. Since every individual’s depression is different, it is often necessary to try several medicines and doses before finding the right one.
One study shows that 67% of people found relief by the fourth medication [5]. Other recent studies have indicated that prescribing antidepressants by trial-and-error without accounting for a patient’s pharmacogenetic profile has an error rate of over 60%, with consequences in safety in efficiency [6]. This trial-and-error process to find the right medication can lead to low patient satisfaction, poor treatment adherence, and increased side effects.
How PGx testing can help optimize antidepressant prescribing
There are real genetically-driven differences in how people metabolize drugs. PGx testing identifies variations in genes that affect how an individual metabolizes and responds to medications. Learning more about drug-gene interactions could provide information on whether to prescribe medication and whether a dosage adjustment is needed. These crucial insights into how a person metabolizes a medication enable healthcare providers to avoid prescribing antidepressants that could produce undesirable outcomes.
The benefits of PGx testing in antidepressant prescribing can be seen in a recent study looking at the pharmacogenomic testing utility in major depressive disorder (MDD) or "depressive disorder not otherwise specified" (DD-NOS) patients treated in psychiatric and primary care settings. According to the results, there is evidence that patients treated at four weeks and who had changes in their medication based on their pharmacogenomic testing improved their depression scores faster than those in the 12-week group [7].
Partnering with LetsGetChecked
LetsGetChecked’s pharmacogenomics solution, myPGx, enables prescribers to select medications with a greater expectation of efficacy and a lower risk of producing adverse drug reactions. Our robust testing panel identifies potential drug-gene interactions for +100 drugs across major disease categories, including behavioral health. Together we can increase the likelihood of a better patient-medication match from the start and decrease costly and inefficient trial-and-error prescribing.
References
- https://www.dbsalliance.org/education/depression/statistics/
- https://www.healio.com/news/hematology-oncology/20210405/pharmacogenetic-testing-may-improve-outcomes-for-patients-with-depression
- https://www.nimh.nih.gov/health/statistics/major-depression
- https://psychnews.psychiatryonline.org/doi/10.1176/appi.pn.2022.08.8.47
- https://www.webmd.com/depression/features/medication-strategies-depression
- http://www.heraldopenaccess.us/openaccess/trial-and-error-versus-personalized-treatment-in-depression-the-power-of-pharmacogenomics
- https://www.genomeweb.com/scan/earlier-pgx-reports-psychiatric-treatment-setting-linked-speedy-symptom-decline-depression#.Y257AHbMLIU
