Need for Pharmacogenomic Testing in Mental Health Care Explored at AMCP 2024

Pharmacogenomics (PGx) is the study of how genetic variations influence individual responses to medication. This area of research has been viewed as a potential strategy for optimizing the efficacy of many medications and mitigating adverse drug reactions (ADRs)—especially in the realm of mental health. To explore the potential of PGx to impact patient outcomes, presenters from the Mayo Clinic gathered on Tuesday, April 16, at the Academy of Managed Care Pharmacy (AMCP) 2024 annual meeting to discuss the evidence supporting the use of PGx in mental health care.

Eric Matey, PharmD, BCAP, MBA, began the talk by presenting concerning data on ADRs experienced by patients. A prospective analysis from 2009 estimated that 120,000 hospitalizations were caused by ADRs annually, which contributed to $3.5 billion in extra yearly medical costs.¹ Furthermore, 1 in 7 patient hospitalizations were complicated by an ADR. There are many factors, Matey added, that can influence ADRs, ranging from drug-drug interactions, diet, and one’s environment to genetics, gender, age, race, and more.

Matey continued the discussion by emphasizing the burden of depression, citing data from 2021 that indicated 14.5 per 100,000 people died by suicide, 15 million people had depression listed as their primary diagnosis during physician visits, and depression was indicated in medical records for 12.5% of emergency department (ED) visits.² Additionally, prior data gathered by the CDC between 2015-2018 reported that over 13% of Americans 18 years and older were taking an antidepressant.³ Matey speculated that these numbers have increased leading into and following the COVID-19 pandemic; however, these analyses demonstrated the widespread importance of addressing the impacts of mental health.

Results from the Sequenced Treatment Alternatives to Relieve Depression (STAR-D) Trial of 2006 showed that there is a need for more effective treatments for patients with major depressive disorder (MDD). This study aimed to investigate how effective depression treatments are in patients diagnosed with MDD and found that 50% of patients respond to first-line therapies; however, only one-third achieved remission.⁴ In cases where first-line therapy was ineffective, a patient’s likelihood of remission decreased with each additional line of therapy (first line: 36.8%; second line: 30.6%; third line, 13.7%; fourth line: 13%). Furthermore, rates of drug intolerance that led to patients discontinuing treatment increased from 16.3% during first-line therapy to 34.1% at fourth-line therapy. Therefore, it was concluded that successive pharmacological treatments had diminished clinical benefits and contributed to more adverse events, suggesting that the best outcomes result from initial therapies. “So here more wasn't better, more actually led to patients dropping out of the study, and less remission as more medications were added,” Matey stated.

AI-generated concept: Pharmacogenomics is the study of how genetic variations influence individual responses to medication | image credit: MuhammadHafiz - stock.adobe.com

Jessica Wright, PharmD, BCACP, followed Matey to discuss the evidence showcasing the benefits of PGx testing in mental health settings. She led her presentation with an overview of the 2021 Review and Consensus on Pharmacogenomic Testing in Psychiatry. Here, the International Society of Psychiatric Genetics reviewed the current literature, prescribing guidelines, and product labels of various medications in psychiatric care, which ultimately supported the use of PGx testing in patients with the following genes: CYP2D6, CYP2C19, HLA-A, HLA-B, and CYP2C9.⁵

Among the organizations that have created guidelines for antidepressant use, Wright referenced the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Dutch Pharmacogenomics Working Group (DPWG) and the FDA.^5,6 These guidelines can inform clinicians on actionable steps they can take dependent on a patient’s PGx test results, including recommendations for drug alternatives or advice for initial dosing.⁷

The legitimacy of these guidelines for improving patient outcomes have been bolstered by studies such as the Genomics Used to Improve Depression Decisions (GUIDED) trial. This randomized, controlled trial analyzed more than 1100 patients with MDD coupled with a poor response to at least 1 antidepressant and found that patients with difficult-to-treat depression experienced greater symptom improvement, rates of remission, and response to medication when switching medications when guided by PGx compared with standard forms of care.⁸ Additionally, Wright referenced a randomized, cross-over, open-label study that demonstrated that PGx guidance in patient treatment could contribute to fewer ADRs compared with standard treatment at 12 weeks (rates of 21.0% vs 27.7%).⁹

With these data in mind, Wright presented the question of whether or not this testing is cost-effective. To explore this point, she reflected on a long-term analysis conducted in 2023, stating, “Looking at cost-effectiveness for major depression, in patients with moderate to severe major depressive disorder, there was another study that saw that PGx testing was predicted to save the health care system $956 million, or almost $5000 per patient. They found that this would bring health gains of 0.064 years and 0.381 quality-adjusted life-years for patients. And so overall...it would be well over 74,000 quality-adjusted life-years that would be gained for these patients.”¹⁰

Wright then echoed a point driven home by Matey that PGx testing, although analyzed through a mental health lens in their presentation, is not solely meant to address mental health and can actually be implemented in various forms of treatment, such as cancer, cardiology, infectious disease, and more, which give the patient outcome and financial results greater implications. “Patients’ genes don't change over their lifetime,” Wright stated, “however, the testing may improve over time. Maybe in 5 to 10 years, 15 years, 20 years, the testing may get better, and at that point, there might be an opportunity to test again. But generally speaking, we have these results, and they can apply to many different medications.”

As the presentation came to a close, Susan Wescott, RPh, MBA, took the stage to discuss her experience in the PGx testing program at Mayo Clinic. Their team gathered medication therapy management (MTM) pharmacists, primary care physicians (PCPs), psychiatrists, and laboratory personnel with the goal of creating a scalable population health program.

They began by piloting a prospecting PGx testing program centered around patients seeking care for mental health. This program was made to test an algorithm for identifying patients at higher risks for drug-gene interactions, as well as reduce ADRs, improve drug efficacy, and use PGx guidelines to inform medication selection.

In their ongoing study, 130 patients had been offered testing as of February 2024, and 30 (23%) followed through with the tests. So far, nearly 17% (n = 6) underwent a medication change in light of their PGx test results. Of this group, 80% (n = 4) of patients had documented symptom improvement in the next 8 months following the change. Wescott acknowledged their limited sample for the time being but posited that “if we can find the right answer for people who come back to the doctor 10,20, 30 times, still seeking an answer, I think this is where you start to see that cost-effectiveness come in. But there's also an outcome piece here that's sort of like MasterCard, you know, you can't measure the value of being able to actually solve this problem for the patient.”

To conclude the talk, Wescott looked toward the future of PGx testing, emphasizing the potential benefits artificial intelligence can provide for the fine-tuning of reporting tools and patient-identifying algorithms. Furthermore, advancing technology offers opportunities to better the flow of processes that educate prescribers, order lab tests, facilitate coordination and communication between clinicians, and more.

References

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2. National Center for Health Statistics. Depression. CDC. Updated November 6, 2023. Accessed April 17, 2024. https://www.cdc.gov/nchs/fastats/depression.htm

3. National Center for Health Statistics. Antidepressant use among adults: United States, 2015-2018. CDC. Updated September 4, 2020. Accessed April 17, 2024. https://www.cdc.gov/nchs/products/databriefs/db377.htm

4. Rush AJ, Trivedi MH, Wisniewski SR, et al. Acute and long-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. AM J Psychiatry. 2006;163(11):1905-17. doi:10.1176/ajp.2006.163.11.1905

5. Bousman CA, Bengesser SA, Aitchison KJ, et al. Review and consensus on pharmacogenomic testing in psychiatry. Pharmacopsychiatry. 2021;54(1):5-17. doi:10.1055/a-1288-1061

6. Bousman CA, Stevenson JM, Ramsey LB, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes and serotonin reuptake inhibitor antidepressants. Clin Pharmacol Ther. 2023;114(1):51-68. doi:10.1002/cpt.2903

7. Table of pharmacogenetic associations. FDA. October 26, 2022. Accessed April 17, 2024. https://www.fda.gov/medical-devices/precision-medicine/table-pharmacogenetic-associations

8. Greden JF, Parikh SV, Rothschild AJ, et al. Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: a large, patient- and rater-blinded, randomized, controlled study. J Psychiatr Res. 2019;111:59-67. doi:10.1016/j.jpsychires.2019.01.003

9. Swen JJ, van der Wouden CH, Manson LE, et al. A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study. Lancet. 2023;401(10374):347-356. doi:10.1016/S0140-6736(22)01841-4

10. Ghanbarian S, Wong GWK, Bunka M, et al. Cost-effectiveness of pharmacogenomic-guided treatment for major depression. CMAJ. 2023;195(44):E1499-E1508. doi:10.1503/cmaj.221785