Abstract
This study was designed to examine the use of pharmacogenomics (PGx) testing in a community-based facility, the adoption of the PGx recommendations by providers, and assess challenges and opportunities for pharmacists in using PGx testing in a real-world setting. This was a retrospective study involving chart reviews of 137 patients with mood disorders who underwent PGx testing between September 2017 and December 2017. Eighty-seven patients who met inclusion and exclusion criteria were analyzed to evaluate the impact of PGx testing on psychotropic medication treatment and to evaluate the PGx test process. PGx test results were used by providers to guide their therapeutic modifications based on the gene-drug interactions identified. Patient medication use increased from 125 to 190 (P < .001) prescriptions. Patient medication belonging to no gene-drug interaction significantly increased from 46.4% to 87.4% (P < .001), medications belonging to moderate and significant gene-drug interaction decreased from 32.8% to 7.9% (P < .001) and 11.2% to 2.1% (P = .012), respectively. 88.5% of patients’ psychotropic medication treatment after PGx testing was consistent with the PGx test report recommendations. The PGx test lengths of time analysis indicated that patient follow-up exceeded the standard time set by guidelines at multiple steps in the test process. There are multiple opportunities for pharmacists to become involved in the PGx testing process to improve patient care.
Keywords: clinical pathways, gene therapy, psychiatric
Introduction
The aims of this study were to examine the use of pharmacogenomics (PGx) testing, assess providers’ adoption of the PGx recommendations and explore challenges of using PGx testing in a community-based facility. PGx is defined as the science that uses information about a person’s genetic makeup or genome to select drug therapies that are likely to work best for that particular person. 1 PGx has transitioned from basic discovery to a tool, PGx test, in which the output is used to guide therapeutic decisions thus improving patient outcomes. 2 Using a PGx test to make patient care decisions is personalized medicine. 2 The primary goals of personalized medicine are to maximize the therapeutic efficacy, minimize the risk of gene-drug interactions, and reduce the chance of adverse drug events. 3 Currently, using a PGx test is not a standard practice in most patient care areas. However, psychiatry has been identified as one of the specialties with the most potential and promise due to multiple therapeutics utilized for treatment, exorbitant psychotropic medication costs plus the therapeutic implications of prescribing genetically inappropriate medications. 4 Due to the 3 to 6 month wait times to obtain an appointment with a psychiatrist, primary care providers have become the first contact when patients decide to seek care. Providing primary care providers with PGx testing to guide psychotropic medications selection would have a positive impact on patients’ outcomes.
The National Institute of Mental Health (NIMH) estimated in 2019 that 51.5 million of US adults live with a mental illness and 13.1 million adults suffer with serious mental illness (SMI). 5 There were only 8.6 million SMI adults who received mental health treatment in either inpatient or outpatient settings which included both patient counseling and medication treatment. 5 In addition to the staggering number of patients suffering from SMI, there is also a shortage of psychiatrists in the United States. 6 Additionally, other researchers found that patients who required more sequential treatments had higher rates of relapse, prolonged disease, decreased probability of achieving remission, increased side-effects, and increased medical costs thereby placing SMI adults at further risk.7 -9 Also, another study estimated that the treatment gap for SMI adults is about 34.5%, and this number unfortunately increased during the pandemic. 10 The burden of mental health treatment is falling overwhelmingly to primary care providers. However, this provider group is not typically trained to manage various mental health conditions.11 -13 Additionally, mental health conditions are difficult to treat and consume providers’ time. Pharmacotherapy can entail frequent changes in medications and dosages to obtain optimal therapy. SMI adults may respond differently to prescribed medications and experience adverse events due to pharmacokinetic and pharmacodynamic differences. 14 The time involvement in taking care of SMI adults to ensure optimal therapy is a major barrier in a community setting.
Overcoming these barriers is paramount to helping patients receive appropriate treatment. PGx testing is a worthwhile tool to help overcome these barriers. Amare et al found that genetic makeup contributed to 31% to 42% of patients’ response variability to treatment. 15 Also, the Clinical Pharmacogenetics Implementation Consortium (CPIC) suggests PGx testing is one of several pieces of clinical information that should be considered before prescribing selective serotonin reuptake inhibitors and tricyclic antidepressants.16,17 Moreover, the US Food and Drug Administration (FDA) published pharmacogenomics biomarkers, which contains more than thirty medications that may require special attention from healthcare providers to effectively treat or monitor patients in neuropsychiatric areas. 18 Stahl also suggested PGx testing could help determine the best treatment options for patients who failed initial psychiatric therapy, 19 and the GUIDED trial indicated that PGx guided care significantly improved response and remission rates in patients with resistant depression compared to treatment as usual. 20 Other studies conducted in outpatient settings also found PGx guided care decreased adverse drug event rates and costs.21,22
To date, there is limited research in determining the status and how to adequately apply PGx testing processes in a community-based facility. The objectives of this study were to evaluate: (1) whether the providers used PGx test results to guide their medication choices and their adoption of the therapeutic modifications based on gene-drug interactions, (2) the change in Patient Health Questionnaire-9 (PHQ-9) scores after therapeutic modifications were implemented, and (3) the length of time between each PGx test step. The length of time between each PGx test step was analyzed to identify potential patient care challenges. Pharmacists, both communities based, and hospital transition of care teams have opportunities to intervene in the steps of the PGx testing to improve processes and patient care.
Methods
This was a retrospective quasi-study design conducted at Crossroad Health Center (CHC) located in Cincinnati, Ohio. CHC is a federally qualified health center that treats all patients regardless of their insurance status and provides primary health care including behavioral health. CHC applies an interdisciplinary practice approach to treat mental health conditions which includes physicians, nurse practitioners, behavioral consultants, plus a pharmacist. Since 2016, a pharmacist at CHC has been at the forefront of utilizing PGx in patient care decisions by implementing PGx testing into the provider’s medication decision process. This pharmacist not only made therapeutic modification recommendations based on PGx test results, but also was involved in pre-test patient counseling, provided test results counseling to patients, and educated other providers and patients about medications. This study was a collaboration between the University of Cincinnati College of Pharmacy (UCCOP) and CHC. IRB approval for the study was granted through UC. The patient data utilized was between September and December 2017 and collected by the researchers between January and April 2018; PHQ-9 data collection was extended to December 2018.
The PGx test used at CHC was the GeneSight® Psychotropic Test, a product of Myriad Genetics, located in Mason, Ohio. The GeneSight® test applies a proprietary algorithm based on numerous clinical studies and follows guidelines and regulations established by FDA, Pharmacogenomics Knowledge Base, CPIC, and the Dutch Pharmacogenetic Working Group to determine patients’ clinically actionable gene-drug interactions. 23 The GeneSight® test classifies medications in the categories of “use as directed,” which means no gene-drug interaction, “moderate gene-drug interaction,” and “significant gene-drug interaction.” The GeneSight® test report includes clinical considerations based on drug metabolism information, gene-drug interactions, and patient genotype and phenotype data (Appendix 1). The report provides information about which medications may be less likely to work for a patient, which medications may require dose adjustments, and which medications may have increased risks of adverse drug events based on the patient’s genetic makeup. The patient reports are posted on the GeneSight® website for easy provider access. The CHC providers had been using this test for at least 6 months and were comfortable with the GeneSight® process.
Patients included in this study were CHC patients who were willing to take a PGx test, who were prescribed psychotropic medication(s) for a mood disorder either before and/or after PGx testing and those who completed all 4 PGx test steps. Exclusion criteria for the PHQ-9 outcome were patients who were diagnosed with bipolar disorder, patients who did not have PHQ-9 scores before and after the PGx test, or the PHQ-9 scores were spaced less than 47 days (including 5 days for the DNA sample and report processing time) or more than 365 days apart. For most psychotropic medications, taking them for less than 28 to 42 days (4-6 weeks) does not allow patients to receive the full medication response. 24
Once patients qualified for PGx testing, providers conducted a pre-test counseling session, received signed consent from patients, submitted the PGx test order online, and collected the patients’ DNA samples using a mouth swab which was sent to the GeneSight® lab. There were 4 PGx test steps (Figure 1). At Step 1, patients came to the clinic with a chief complaint of having a mental health problem. CHC providers evaluated patients’ medical histories and determined PGx test candidacy based on the following criteria: patient treatment failure with at least 1 psychotropic medication, had undesirable side effect(s), or patients hesitated to start a medication. At CHC, patients typically had Medicaid and Medicare coverage and had to be willing to take a PGx test. Once patients qualified for PGx testing, providers conducted a pre-test counseling session, received signed consent from patients, submitted the PGx test order online, and collected the patients’ DNA samples using a mouth swab which was sent to the GeneSight® lab. The GeneSight® lab states patient reports would be posted online within 48 hours after receiving the DNA samples. 24 At Step 2, the providers retrieved the test reports and scheduled the patients’ appointments. At Step 3, the providers reviewed the results with patients and had the opportunity to make therapeutic modifications. At Step 4, patients returned to CHC to assess the effect of the therapeutic modifications.
Figure 1.
PGx test steps at CHC.
Since the electronic medical record (EMR) could not be downloaded, the data were manually retrieved and keyed in by four UCCOP PharmD students. Microsoft Excel was used in recording these data. All data were verified by the other PharmD students to ensure accuracy. The recorded data included truncated patient name, gender, date of birth, disease state, treating clinician, history of smoking, history of drinking alcohol, illegal substance use, date of PGx test, date of receiving PGx results, date of PGx consultation with providers, date of follow up with providers, psychotropic medications, and PHQ9 score before and after the PGx test, reasons for psychotropic medication modifications, and physician notes for each visit. Additionally, the categories of gene-drug interactions and medications’ clinical considerations were collected from the PGx test reports.
For the first research objective (the use of PGx test results to guide providers regarding medication choices and the adoption of the therapeutic modifications based on gene-drug interactions), the patients’ psychotropic medications prescribed before and after the PGx test were compared with patient charts. The therapeutic modifications made after the PGx test were analyzed in the categories of (1) initiated new medication—provider initiated a new psychotropic medication, (2) dose adjustment—patients remained on the same psychotropic medication(s), the dose was either increased or decreased, (3) no adjustment—patients remained on the same psychotropic medications with no change in dose, and (4) discontinued medication—discontinued psychotropic medication. Based on the PGx test reports, all the psychotropic medications used before and after the PGx test were further classified into the categories of gene-drug interaction of “no gene-drug interaction,” “moderate gene-drug interaction,” and “significant gene-drug interaction.” The Wilcoxon test was used and the analysis determined whether the results of patients’ PGx tests guided the therapeutic modifications providers made based on gene-drug interactions and whether these modifications were consistent with the PGx test recommendations.
For the second research objective was the PHQ-9 score change used to assess depression before and after therapeutic modifications. PHQ-9 scores of 5, 10, 15, and 20 represent mild, moderate, moderately severe, and severe depression, respectively. The PHQ-9 scores were collected before the PGx test and at least 6 weeks after therapeutic modifications. The paired sample t-test was utilized to determine the PHQ-9 score change.
For the third research objective, the length of time between each PGx test step was calculated using the dates recorded in the EMR. Four dates (steps) were used, Step 1—The date the consent form was signed, Step 2—the date the PGx test report was received by CHC, Step 3—the date the patient spoke with a provider regarding their PGx test results, and Step 4—the date the patient came back to the clinic for follow up with their provider to assess the effect of any therapeutic modifications. The number of days between each step was compared to the desired length of time listed on the GeneSight® website, the American Psychiatric Association, and the National Institute for Clinical Excellence guideline recommendations.24 -26 The desired length of time was considered as the PGx Standard Duration for measurement purposes (Figure 1).
Results
There were 137 patient charts reviewed (Figure 2). A total of 50 patients were excluded from the study for not meeting criteria, which included 27 patients who did not meet inclusion criteria, and 23 patients who did not complete all 4 PGx steps, thus 87 patients remained in the analysis. Table 1 shows the patients’ demographics of those included in the study.
Figure 2.
Patient enrollment process.
Table 1.
Demographics of Study Patients.
Female—n, % | 69 (79.3) |
Mean age | 36 (SD = ±13.9) |
Male—n, % | 18 (20.7) |
Mean age | 41.5 (SD = ±14.6) |
History of smoking | Number, % |
Never smokers | 27 (31.0) |
Former smokers † | 15 (17.3) |
Current smokers | 43 (49.4) |
Missing data | 2 (2.3) |
History of drinking | Number, % |
Never | 50 (57.5) |
Occasionally ‡ | 29 (33.3) |
Moderate or heavy § | 6 (6.9) |
Missing data | 2 (2.3) |
History of illicit substance | Number, % |
Never | 73 (83.9) |
Use of any illicit drugs | 10 (11.5) |
Missing data | 4 (4.6) |
Total | 87 (100) |
Note. All of the information was collected from the patients’ clinical charts.
Former-smokers—patient did not smoke in the last month, but has smoked previously.
Occasional—patient drinks 1 to 2 times per week or clinical chart indicates occasional alcohol use.
Moderate or heavy—patient drinks more than 2 times per week or clinical chart indicates moderate to heavy alcohol use.
Tables 2 and 3 indicate the providers’ adoption of the PGx test results: (1) comparative number of medications prescribed before versus after the PGx test was given and (2) the number and types of therapeutic modifications made after the PGx test results were available. Analysis indicated that 125 medications were prescribed to patients before the PGx test, while 190 medications were prescribed after the PGx test (P < .0001). Those medications were then categorized by gene-drug interaction. The number of medications prescribed with no gene-drug interaction significantly increased from 55 medications before the PGx test to 166 medications after the PGx test (P < .0001). Additionally, the number of medications prescribed with moderate and significant gene-drug interactions were significantly decreased from 44 to 15 and 12 to 5 (P < .001, P < .012) respectively. Table 3 depicts there were 263 total therapeutic modifications: 138 medications were newly initiated, 10 medications with a dose increase, and 2 medications with a dose decrease, 40 medications continued with the same dose, and 73 medications were discontinued. Finally, Table 2 shows the patients’ PHQ-9 scores (n = 59). The average PHQ-9 score before the therapeutic modifications was 16.1 (SD = ±5.3) which significantly decreased to 11.2 (SD = ±5.9) after the therapeutic modifications (P < .001).
Table 2.
Number of Medication Prescribed Before and After PGx Test by Gene-Drug Interaction.
Before PGx test (n, %) | After PGx test and medication modified (n, %) | P-value | |
---|---|---|---|
No gene-drug interaction | 55 (44.0) | 166 (87.4) | <.0001 |
Moderate gene-drug interaction | 44 (35.2) | 15 (7.9) | <.0001 |
Significant gene-drug interaction | 14 (11.2) | 4 (2.1) | .012 |
No proven genetic markers † | 12 (9.6) | 5 (2.6) | n/a |
Total | 125 (100) | 190 (100) | <.0001 |
Analysis of PHQ-9 score (patients, n = 59) | |||
Mean | 16.1 | 11.2 | <.0001 |
SD | 5.3 | 5.9 | n/a |
Gabapentin, topiramate, lithium did not have proven genetic marker and were not evaluated by the PGx test.
Table 3.
Therapeutic Modifications Made by the Providers After PGx Test Results.
Therapeutic modifications (n, %) | ||
---|---|---|
Initiated new medication | 138 (52.5) | |
Dose adjustment | ||
Increase dose | 10 (3.8) | |
Decrease dose | 2 (0.8) | |
No adjustment | 40 (15.2) | |
Subtotal | 190 (72.2) | |
Discontinued medication | 73 (27.8) | |
Total | 263 (100) |
Before the PGx test was administered, there were 72 out of a total of 87 patients prescribed psychotropic medications. Tables 4 and 5 further indicates the providers’ adoption of PGx test results. Table 4 shows 72 patients’ therapeutic modifications related to gene-drug interaction identified by the PGx test. Providers made therapeutic modifications for 43 patients who had gene-drug interactions and 17 patients with no gene-drug interaction. Twelve patients continued their current therapy regardless of whether there were identified gene-drug interactions. Table 5 displays patients’ therapeutic modifications and their consistency with PGx test recommendations. Overall, 77 patients had therapeutic modifications consistent with their PGx test recommendations. Fourteen out of 15 patients who had not been prescribed psychotropic medications prior to PGx testing, were initiated on psychotropic medications consistent with the PGx test recommendations.
Table 4.
Patients who Received Therapeutic Modifications Categorized by Gene-Drug Interaction.
Patient (n = 72) | Have gene-drug interaction | No gene-drug interaction | n |
---|---|---|---|
Therapeutic modifications made | 43 (59.7%) | 17 (23.6%) | 60 |
No therapeutic modifications made | 5 (6.9%) | 7 (9.7%) | 12 |
Total Patients | 48 | 24 | 72 |
Table 5.
Patients’ Therapeutic Modifications after PGx Test—Consistency with PGx Test Recommendations.
Consistent with PGx test recommendations (n, %) | Inconsistent with PGx test recommendations (n, %) | ||
---|---|---|---|
Patients on psychotropic medications before PGx test (n = 72) | |||
Medication adjustment | 56 (64.4) | 4 (4.6) | 60 |
No adjustment | 7 (8.1) | 5 (5.8) | 12 |
Patients not on psychotropic medications before PGx test (n = 15) | |||
Initiated new medication | 14 (16.1) | 1 (1.2) | 15 |
Total patients | 77 (88.5) | 10 (11.5) | 87 (100%) |
Table 6 shows the length of time between each PGx step compared to the PGx standard duration. Between Steps 1 and 2, 66 patients’ PGx test reports were available within 5 days and 20 patients’ PGx test reports exceeded 5 days. Between Steps 2 to 3, 17 patients received PGx test counseling from their providers within 7 days and 63 patients waited more than 7 days to receive counseling. After patient counseling (Steps 3-4), there were 16 patients who came to the follow-up visit in less than 28 days. Twenty-eight patients who followed up with their providers within the standard 28 to 42 days and 33 patients took longer than 42 days to come for a follow-up visit. The decreasing sample size between these steps, 86 beginning from Step 1 to 77 at the end of Step 4, was due to missing dates in some patient charts.
Table 6.
Length of Time Between PGx Test Steps.
Step | Number of days | Number of patients | ||
---|---|---|---|---|
PGx standard duration | Median (Range) | Within expected duration (n, %) | Duration more than expected | |
Steps 1-2 | ||||
Step 1: PGx test ordered—Step 2: PGx test result available to providers (n = 86) † | 5 | 3 (1-23) | 66 (76.7) | 20 (23.3) |
Steps 2-3 | ||||
Step 2: PGx test result available to providers—Step 3: PGx test results reviewed with patient, possible therapeutic modifications (n = 80) † | 7 | 13 (1-154) | 17 (21.3) | 63 (78.8) |
Steps 3-4 | ||||
Step 3: PGx test results reviewed with patient, possible therapeutic modifications—Step 4: Patients followed-up with providers (n = 77) † | 28-42 | 35 (6-268) | 28 (36.4) | 49 (43.6) |
Total | 40-54 | 51 |
Patient visit dates were missing from the patient chart.
Discussion
This study focused on the use of PGx testing in a community facility. It assessed whether providers used PGx test results in making therapeutic modifications and explored the challenges of using PGx testing in a real-world setting. This is a unique opportunity for pharmacists’ involvement to improve the clinical process.
The analysis suggested the PGx test results were used by providers to guide their medication choices when prescribing psychotropic medications and when they made therapeutic modifications based on the gene-drug interactions identified. There was a significant increase in prescribing psychotropic medications—initiating new therapy in patients who were not receiving current psychotropic treatment before the PGx test. Not only was there an increased number of medications prescribed after the PGx test, but also medications were prescribed with no gene-drug interaction which is theoretically better for patients. Moreover, the utilization of medications categorized as moderate and significant gene-drug interactions were significantly decreased. Choosing medications with moderate or significant gene-drug interactions increases the chance for patients not to have the desired response to medications or experience adverse events. It should be noted that, medications categorized as “moderate or significant gene-drug interaction” do not necessarily mean the medications cannot be used for patients. 24 It depends on the patients’ conditions and the providers’ clinical considerations. In this study, most patients’ therapeutic modifications were consistent with the PGx test recommendations.
This study also evaluated the lengths of time between the PGx test steps to assess the potential challenges in carrying out PGx testing in a real-world setting. The results indicated that many patients did not complete each step in the PGx standard duration timeframe. For example, in Step 2, 75.7% of patients did not meet the 7-day Standard Duration to review their PGx test reports. In fact, the median was 13 days, but some patients waited up to 154 days to meet with their providers. The length of time between receiving the PGx test report (Step 2) and provider-patient consultation (Step 3) also took longer than desired. From the patients’ charts, no explanation was documented. In follow up discussions with the providers at the CHC clinic, the main reason in delay of PGx test progression was due to patient reports of being busy with work or family.
For the 87 patients who finished all 4 PGx standard steps, there were 19 (21.8%) patients who did not follow up by coming back to the clinic after 12 weeks of treatment. Even the GUIDED trial reports 16.5% patient loss after 8 weeks of treatment, and, unfortunately, the GUIDED trial did not give an explanation about loss of follow-up during the treatment process. In addition, 23 of 137 (16.8%) patients who did not finish PGx Steps 2 through 4 were also excluded from this study. In real-world situations, it is important to retain these patients to maintain their therapy. A process to improve patient follow-up and increase patient retention is necessary. Pharmacists have a unique opportunity to intervene here. For example, pharmacists can proactively manage the PGx process to reduce delay between the PGx steps, thus achieving optimal therapy more quickly. They can also, increase patient retention by making phone calls and speaking with patients directly, if they are unable to come to the clinic. Kim et al 27 showed a practice model where pharmacists consulted patients who received the PGx test by an MTM telephone call. Another study by Cohen et al 28 and associates found that a pharmacist-led telehealth disease management program can improve patients’ medication adherence for antidepressants. Using the telephone to review the PGx test results is an easy way for patients to review their therapy. Pharmacists can emphasize the importance of medication use and solve other patient barriers that may delay follow-up. Increased communication will also help build patient trust and loyalty with the health care facility and health care providers. Motivational interviewing is another tool that pharmacists could utilize to explore and solve patients’ specific barriers to follow-up. Even trained student pharmacists can be involved in the PGx step process. They can provide patients both drug and disease information, medication education, and telehealth MTM follow up.
There were several limitations to this study. CHC mainly serves a low-income population, and patients who received the PGx test were limited to those who had Medicare and Medicaid which covered PGx testing. Commercial insurance coverage is very limited and only covers PGx testing in limited situations. Issues found in this low-income population may not be generalizable to other patient populations. Additionally, some patients might be misdiagnosed with depression instead of bipolar disorder, for example, or vice versa. This would lead to suboptimal treatment regardless of whether the provider followed the PGx test result recommendations. Furthermore, the sample size decreased as patients progressed through the 4 PGx steps. Methods to retain the patients would make this study more robust, along with having a larger sample size. Finally, the medication categories used before and after therapeutic modification were statistically different but may not be clinically significant. Future PGx studies documenting the reduction of adverse drug effects and medication adherence is needed. Patients may have better medication adherence if they experience fewer adverse effects.
Conclusion
PGx testing is an important tool to guide medication choices in psychotropic therapy. Pharmacists’ involvement, both community based and hospital transition of care teams, could increase the efficiency of the process, increase patient retention during the PGx steps, thereby improving patient outcomes.
Acknowledgments
Special thanks to Dr. Carrie Hoefer, Dr. Nihal El Rouby, Mr. Lucas Scharf da Costa.
Appendix 1
PGx Report Definitions from Genesight. 29
Metabolizer phenotype | Potential consequence |
---|---|
Intermediate metabolizer | Reduced enzyme activity |
Poor metabolizer | Markedly reduced or absent enzyme activity |
Extensive metabolizer | Normal enzyme activity |
Ultra-rapid metabolizer | High enzyme activity |
Clinical consideration30† | |
1) Serum level may be too high, lower dose may be required | |
2) Serum level may be too low, higher doses may be required | |
3) Difficult to predict dose adjustments due to conflicting variations in metabolism | |
4) Genotype may impact drug mechanism of action and result in reduced efficacy | |
5) Not currently in use in the United States | |
6) Use of this drug may increase risk of side effects | |
7) Serum level may be too low in smokers | |
8) FDA label identifies a potential gene-drug interaction for this medication | |
9) Per FDA label, this medication is contraindicated for this genotype | |
10) This medication does not have clinically proven genetic markers that allow it to be categorized |
Clinical considerations collected from the GeneSight® PGx test report.
Footnotes
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
ORCID iD: Jingyi Wang
https://orcid.org/0000-0001-8958-6041
References
- 1. National Human Genome Research Institute. Frequently asked questions about pharmacogenomics. 2020. Accessed July 10, 2020. https://www.genome.gov/FAQ/Pharmacogenomics#al-1
- 2. Ross S, Anand SS, Joseph P, Paré G. Promises and challenges of pharmacogenetics: an overview of study design, methodological and statistical issues. JRSM Cardiovasc Dis. 2012;1(1):1-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Xie HG, Frueh FW. Pharmacogenomics steps toward personalized medicine. Per Med. 2005;2(4):325-337. [DOI] [PubMed] [Google Scholar]
- 4. de Leon J, Arranz MJ, Ruaño G. Pharmacogenetic testing in psychiatry: a review of features and clinical realities. Clin Lab Med. 2008;28(4):599-617. [DOI] [PubMed] [Google Scholar]
- 5. National Institute of Mental Health. Prevalence of any mental illness, mental illness. September, 2021. https://www.nimh.nih.gov/health/statistics/mental-illness (Substance Abuse and Mental Health Services Administration. (2020). Key substance use and mental health indicators in the United States: Results from the 2019. National Survey on Drug Use and Health (HHS Publication No. PEP20-07-01-001). Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. Retrieved from https://www.samhsa.gov/data/sites/default/files/reports/rpt29393/2019NSDUHFFRPDFWHTML/2019NSDUHFFR1PDFW090120.pdf.) [Google Scholar]
- 6. Cunningham PJ. Beyond parity: Primary Care Physicians' Perspectives on access to mental health care. Health Aff. 2009;28(3):w490-w501. [DOI] [PubMed] [Google Scholar]
- 7. Novick D, Montgomery W, Vorstenbosch E, Moneta MV, Dueñas H, Haro JM. Recovery in patients with major depressive disorder (MDD): results of a 6-month, multinational, observational study. Patient Prefer Adherence. 2017;11:1859-1868. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Warden D, Rush AJ, Trivedi MH, Fava M, Wisniewski SR. The STAR*D Project results: a comprehensive review of findings. Curr Psychiatry Rep. 2007;9(6):449-459. [DOI] [PubMed] [Google Scholar]
- 9. Mrazek DA, Hornberger JC, Altar CA, Degtiar I. A review of the clinical, economic, and societal burden of treatment-resistant depression: 1996-2013. Psychiatr Serv. 2014;65(8):977-987. [DOI] [PubMed] [Google Scholar]
- 10. Ettman CK, Cohen GH, Abdalla SM, et al. Persistent depressive symptoms during COVID-19: a national, population-representative, longitudinal study of U.S. adults. Lancet Reg Health Am. 2022;5:100091. doi: 10.1016/j.lana.2021.100091 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Daly M, Sutin AR, Robinson E. Depression reported by US adults in 2017–2018 and March and April 2020. J Affect Disord. 2021;278:131-135. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Pappa S, Ntella V, Giannakas T, Giannakoulis VG, Papoutsi E, Katsaounou P. Prevalence of depression, anxiety, and insomnia among healthcare workers during the COVID-19 pandemic: a systematic review and meta-analysis. Brain Behav Immun. 2020;92:245-907. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Xiong J, Lipsitz O, Nasri F, et al. Impact of COVID-19 pandemic on mental health in the general population: a systematic review. J Affect Disord. 2020;277(1):55-64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Ware K, Tillery E, Linder L. General pharmacokinetic/pharmacodynamic concepts of mood stabilizers in the treatment of bipolar disorder. Ment Health Clin. 2016;6(1):54-61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Amare AT, Schubert KO, Baune BT. Pharmacogenomics in the treatment of mood disorders: strategies and opportunities for personalized psychiatry. EPMA J. 2017;8(3):211-227. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Hicks JK, Bishop JR, Sangkuhl K, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and dosing of selective serotonin reuptake inhibitors. Clin Pharmacol Ther. 2015;98(2):127-134. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Hicks JK, Sangkuhl K, Swen JJ, et al. Clinical pharmacogenetics implementation consortium guideline (CPIC) for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants: 2016 update. Clin Pharmacol Ther. 2017;102(1):37-44. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Administration FDA gov. Table of pharmacogenomic biomarkers in drug labeling. 2020. https://www.fda.gov/drugs/scienceresearch/ucm572698.htm
- 19. Stahl SM. Psychiatric pharmacogenomics: how to integrate into clinical practice. CNS Spectr. 2017;22(1):1-4. [DOI] [PubMed] [Google Scholar]
- 20. 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] [PubMed] [Google Scholar]
- 21. Hall-Flavin DK, Winner JG, Allen JD, et al. Utility of integrated pharmacogenomic testing to support the treatment of major depressive disorder in a psychiatric outpatient setting. Pharmacogenet Genomics. 2013;23(10):535-548. [DOI] [PubMed] [Google Scholar]
- 22. Groessl EJ, Tally SR, Hillery N, Maciel A, Garces JA. Cost-effectiveness of a pharmacogenetic test to guide treatment for major depressive disorder. J Manag Care Spec Pharm. 2018;24(8):726-734. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. GENESIGHTCOM, The GeneSight® psychotropic combinatorial algorithm. 2020. Accessed March 4, 2021. https://genesight.com/white-papers/the-genesight-psychotropic-combinatorial-algorithm/
- 24. GENESIGHTCOM, FAQs about the GeneSight test. 2020. Accessed March 4, 2021. https://genesight.com/clinician-faq/
- 25. National Collaborating Centre for Mental Health UK. Depression in adults with a chronic society. NICE Clinical Guidelines No. 91. 2010. [Google Scholar]
- 26. Armstrong C. APA releases guidelines on treatment of patients with major depressive disorder. Am Fam Phys. 2011;283(10):1219. [Google Scholar]
- 27. Kim K, Magness JW, Nelson R, Baron V, Brixner DI. Clinical utility of pharmacogenetic testing and a clinical decision support tool to enhance the identification of drug therapy problems through medication therapy management in polypharmacy patients. J Manag Care Spec Pharm. 2018;24(12):1250-1259. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Cohen LB, Taveira TH, Wu WC, Pirraglia PA. Pharmacist-led telehealth disease management program for patients with diabetes and depression. J Telemed Telecare. 2020;26(5):294-302. doi: 10.1177/1357633X18822575 [DOI] [PubMed] [Google Scholar]
- 29. Belle DJ, Singh H. Genetic factors in drug metabolism. Am Fam Physician. 2008; 77(11):1553-1560. [PubMed] [Google Scholar]
- 30. GeneSight.com. How can I use the clinical considerations to help interpret the GeneSight® report? Accessed July 13, 2020. https://genesight.com/how can i use the clinical considerations to help interpret the gene sight report/ [Google Scholar]