COVID-19 has caused major physical and psychological harm for millions of Americans.
For many individuals with cancer, the trauma associated with their diagnosis has been compounded by the emotional burden of the pandemic.
A survey of U.S. adults with cancer by Ettman and colleagues identified threefold higher depression symptom prevalence during the pandemic than before.
More than half of respondents reported at least mild depression during the pandemic compared with 25% prior; the percentage of respondents who reported moderate to severe depression increased from 8.5% to 28%.
Early screening and specialized interventions to manage these symptoms among people with cancer can improve quality of life and potentially reduce cancer mortality. A multidisciplinary approach that involves social support, behavioral therapy, integrative medicine and pharmacotherapy can improve mental health significantly.
Jai N. Patel
The most widely used pharmacotherapy classes are selective serotonin reuptake inhibitors (SSRIs) and serotonin norepinephrine reuptake inhibitors (SNRIs), but response to therapy is heterogenous.
Despite advances in the understanding of psychopharmacology, up to 50% of patients with depression do not respond to first-line therapy, and as few as one-third of those treated with SSRIs achieve remission or absence of symptoms. Further, 25,000 patients in the U.S. present to the ED each year due to antidepressant-related adverse events.
Lack of predictive biomarkers is one potential reason for heterogeneity in treatment response.
Pharmacogenetics (PGx) — the impact of genetics on drug response — may provide valuable insights.
Genetic variants contribute to nearly 50% of antidepressant response rates. More than 10 medications approved for treating depression have PGx-related information for the genes CYP2D6 and/or CYP2C19 in the product label.
Greater awareness and concise guidelines help facilitate the use of PGx in clinical practice.
The Clinical Pharmacogenetic Implementation Consortium (CPIC) — an international group of experts in PGx who develop peer-reviewed guidelines on how to translate genomic findings into actionable prescribing decisions — published guidelines related to use of many antidepressants for treating major depression.
Impact of PGx on drug pharmacokinetics
Genetic polymorphisms that cause variations in drug metabolism may contribute to altered drug exposure and, thus, drug failure or increased risk for toxicities.
The cytochrome P450 (CYP) enzymes play a major role in the oxidative metabolism of antidepressants; in fact, CYP2C19, CYP2D6 and CYP3A4 account for nearly 75% of total metabolism of all antidepressants.
CYP2C19 plays a major role in the metabolism of citalopram, escitalopram and sertraline. Data suggest clearance for these drugs is 56% to 60% of normal for patients who harbor two nonfunctional alleles (eg, poor metabolizers).
These individuals are at increased risk for supratherapeutic drug concentrations. This may increase toxicity risk, including QT prolongation.
Alternatively, those who carry the *17 allele — which results in rapid or ultra-rapid metabolism — have 120% to 150% increased clearance, resulting in lower plasma concentrations and higher likelihood of subtherapeutic drug concentrations, potentially resulting in drug failure.
CYP2D6 metabolizes many SSRIs, SNRIs and tricyclic antidepressants. The clearance of tricyclic antidepressants — including amitriptyline and nortriptyline — is 50% to 67% lower in CYP2D6 poor metabolizers compared with normal metabolizers. Alternatively, the clearance is 130% to 190% higher among rapid metabolizers compared with normal metabolizers.
Paroxetine and venlafaxine also are metabolized by CYP2D6. Like SSRIs metabolized by CYP2C19, low drug concentrations are associated with drug failure, whereas high drug concentrations are associated with increased toxicity risk.
Vortioxetine, a newer SSRI, is metabolized by multiple isozymes, including CYP2D6. The package insert suggests a maximum recommended dose in CYP2D6 poor metabolizers of 10 mg per day based on pharmacokinetic data submitted as part of the original new drug application.
A systematic review and meta-analysis by Milosavljevi and colleagues that encompassed 94 studies and 8,379 individuals showed that aripiprazole, haloperidol and risperidone drug exposure was significantly associated with CYP2D6 phenotype, whereas escitalopram and sertraline drug exposure was significantly associated with CYP2C19 phenotype.
Researchers noted exposure differences for many other antidepressants and antipsychotics, but they were marginal or based on fewer than three independent studies.
PGx and treatment response
At least six randomized trials have evaluated the impact of PGx-guided antidepressant management on treatment response and disease remission.
Bousman and colleagues conducted a meta-analysis of five of these trials that included 1,737 patients, 887 of whom received PGx-guided therapy. Results showed those who received PGx-guided therapy were 1.71 (95% CI; 1.17-2.48) times more likely to achieve symptom remission than those who received usual treatment.
In the largest randomized trial, Greden and colleagues used the 17-item Hamilton Rating Scale for Depression (HAM-D17) to evaluate response and remission.
Researchers reported no statistically significant difference in the primary endpoint — symptom improvement at week 8 — between the PGx-guided and control groups (27.2% vs. 24.4%). However, results showed significant improvements in response (26% vs. 19.9%; P =.013) and remission (15.3% vs. 10.1%; P=.007) with PGx-guided therapy.
Those taking medications incongruent with PGx results prior to baseline who switched to congruent medications by week 8 appeared more likely to experience symptom improvement (33.5% vs. 21.1%; P=.002), response (28.5% vs. 16.7%; P=.036) and remission (21.5% vs. 8.5%; P=.007) than those who remained on incongruent medications.
A randomized trial by Bradley and colleagues compared standard care with PGx-guided treatment for 685 patients with depression and/or anxiety based on the NeuroIDgenetix test, which includes 10 genes for over 40 medications.
Researchers performed the HAM-D17 and Hamilton Rating Scale for Anxiety (HAM-A) at baseline, as well as at 4, 8 and 12 weeks.
Among patients with depression, results showed significantly higher response rate (OR = 4.72; 95% CI, 1.93-11.52) and remission rate (OR = 3.54; 95% CI, 1.27-9.88) in the PGx-guided group at 12 weeks.
Among patients with anxiety, investigators reported meaningful improvement in HAM-A scores at 8 weeks and 12 weeks (P = .02 for both), along with a higher response rate (OR = 1.76; 95% CI, 1.03-2.99), with PGx-guided treatment.
A randomized trial by Perlis and colleagues — published after the meta-analysis — included 304 patients with nonpsychotic major depressive disorder. Researchers randomly assigned study participants to assay-guided treatment (n = 151) or usual treatment (n = 153).
Results showed no significant difference in HAM-D17 at 8 weeks between groups; however, fewer individuals in the PGx-guided group experienced worsening of depressive symptoms, and those who received treatment concordant with PGx results had greater likelihood of remission.
Although these randomized trials appear to show benefit with PGx-guided therapy, it is important to note most patients enrolled had already failed multiple lines of therapy. It is well-recognized that depression becomes more difficult to treat after patients have progressed through several lines of treatment.
Theoretically, preemptive PGx testing at the time of diagnosis would further improve the likelihood of achieving response and remission quicker; however, this has not been addressed in a randomized controlled trial.
A new standard?
Many caveats must be considered before adopting routine PGx testing for treatment of major depression.
There is uncertainty about testing algorithms and treatment recommendations in some prior randomized trials that used commercial tests. In addition, most trials have had overrepresentation of women, middle-aged adults (aged 40 to 50 years) and those with a European background.
Thus, the generalizability of these findings to any individual patient in clinical practice may be limited or vary considerably based on patient characteristics.
These trials also did not address at what point in care a clinician should consider ordering a PGx test. And, for results to be used downstream for subsequent medications, there must be clinical decision support integrated into the electronic medical record with evidence-based recommendations provided to the clinician in real time.
It often takes 6 to 8 weeks to determine treatment response to antidepressants. That is valuable time lost if a patient is prone to drug failure, and it can have a significant impact on quality of life and cost. Progression of depressive symptoms during this time can be devastating.
Based on compelling clinical data, CPIC guidelines and FDA guidance, many health systems have adopted PGx testing to guide treatment strategies for depression. However, the FDA has had concerns about how these tests have been used and marketed, prompting warning letters to specific labs suggesting that “the relationship between DNA variations and the effectiveness of antidepressant medication has never been established.”
Nonetheless, the package inserts for many antidepressants — including escitalopram, which was cited as a specific example by the FDA — describe the relationship between CYP2C19 and drug concentrations. Many other antidepressants have been described in recent PGx tables published by the FDA — including citalopram, escitalopram, paroxetine, venlafaxine and vortioxetine — with varying levels of evidence.
Cost also is an important factor when considering a new potentially disruptive technology in practice.
Maciel and colleagues analyzed costs of PGx testing for depression in a real-world setting. They calculated a $3,962 annual savings per patient, assuming a $2,000 test cost. However, current PGx tests are much cheaper and multigene tests are likely to result in significantly more savings.
Based on established evidence and CPIC guidelines, CMS declared a local coverage determination that covers multigene testing for drug/gene pairs with CPIC level A or B evidence, with certain caveats. United Healthcare also issued a coverage policy for multigene panels specifically for antidepressants and antipsychotics, also with caveats.
Conclusion
There is a major unmet clinical need for better methods of pharmacotherapy selection for individuals diagnosed with major depression.
Mental health is a significant public health issue that has affected millions of people across the globe, further propagated by the COVID-19 pandemic — especially for those with preexisting chronic conditions, such as cancer.
PGx-guided depression treatment may be considered as part of routine clinical practice to improve treatment response for the following reasons:
There is strong evidence that CYP2D6 and CYP2C19 phenotypes affect drug pharmacokinetics.
There is moderate to strong evidence that pharmacokinetics and PGx impact response and/or toxicity risk for some drug-gene pairs.
There is moderate evidence that PGx-guided treatment improves clinical outcomes, although it is undetermined if preemptive testing prior to initial drug selection would improve outcomes further.
There are many drugs to select from that are otherwise considered clinically similar.
Response is not immediate; therefore, the trial-and-error approach can prove detrimental to patients.
There is increasing payer coverage, suggesting potential cost savings.
References:
Bousman CA, et al. Pharmacogenomics. 2019;doi:10.2217/pgs-2018-0142. Bradley P, et al. J Psychiatr Res. 2018;doi:10.1016/j.jpsychires.2017.09.024. CMS. Local coverage determination (LCD): MolDX: Pharmacogenomics Testing (L38294). Available at: https://www.cms.gov/medicare-coverage-database/details/lcd-details.aspx?LCDId=38294&ver=16&DocID=L38294&SearchType=Advanced&bc=EAAAAAgAAAAA&. Accessed March 23, 2021. Ettman CK, et al. JAMA Netw Open. 2020;doi:10.1001/jamanetworkopen.2020.19686. FDA. The FDA warns against the use of many genetic tests with unapproved claims to predict patient response to specific medications: FDA safety communication. Available at: https://www.fda.gov/medical-devices/safety-communications/fda-warns-against-use-many-genetic-tests-unapproved-claims-predict-patient-response-specific. Accessed March 23, 2021. Giese-Davis J, et al. J Clin Oncol. 2011;doi:10.1200/JCO.2010.28.4455. Greden JF, et al. J Psychiatr Res. 2019;doi:10.1016/j.jpsychires.2019.01.003. Hampton LM, et al. JAMA Psychiatry. 2014;doi:10.1001/jamapsychiatry.2014.436. Hicks JK, et al. Clin Pharmacol Ther. 2020;doi:10.1002/cpt.1661. Jazieh AR, et al. JCO Glob Oncol. 2020;doi:10.1200/GO.20.00351. Maciel A, et al. Neuropsychiatr Dis Treat. 2018;doi:10.2147/NDT.S145046. Perlis RH, et al. Depress Anxiety. 2020;doi:10.1002/da.23029. Stingl JC, et al. Mol Psychiatry. 2013;doi:10.1038/mp.2012.42. Tansey KE, et al. Biol Psychiatry. 2013;doi:10.1016/j.biopsych.2012.10.030. United Healthcare. Pharmacogenetic Testing. Available at: https://www.uhcprovider.com/content/dam/provider/docs/public/policies/comm-medical-drug/pharmacogenetic-testing.pdf. Accessed March 23, 2021.
For more information:
Jai N. Patel, PharmD, BCOP, CPP, is chair of cancer pharmacology and associate professor in the division of hematology/oncology at Levine Cancer Institute at Atrium Health. He also is a HemOnc Today Editorial Board Member. He can be reached at jai.patel@atriumhealth.org.