Economic Utility: Combinatorial Pharmacogenomics and Medication Cost Savings for Mental Health Care in a Primary Care Setting

Biomarkers in the Diagnosis and Prediction of Medication Response in Depression and the Role of Nutraceuticals

Depression continues to be a significant and growing public health concern. In clinical practice, it involves a clinical diagnosis. There is currently no defined or agreed upon biomarker/s for depression that can be readily tested. A biomarker is defined as a biological indicator of normal physiological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention that can be objectively measured and evaluated. Thus, as there is no such marker for depression, there is no objective measure of depression in clinical practice. The discovery of such a biomarker/s would greatly assist clinical practice and potentially lead to an earlier diagnosis of depression and therefore treatment. A biomarker for depression may also assist in determining response to medication. This is of particular importance as not all patients prescribed with medication will respond, which is referred to as medication resistance. The advent of pharmacogenomics in recent years holds promise to target treatment in depression, particularly in cases of medication resistance. The role of pharmacogenomics in routine depression management within clinical practice remains to be fully established. Equally so, the use of pharmaceutical grade nutrients known as nutraceuticals in the treatment of depression in the clinical practice setting is largely unknown, albeit frequently self-prescribed by patients. Whether nutraceuticals have a role in not only depression treatment but also in potentially modifying the biomarkers of depression has yet to be proven. The aim of this review is to highlight the potential biomarkers for the diagnosis, prediction, and medication response of depression.

Effectiveness of pharmacogenomics on the response and remission of treatment-resistant depression: a meta-analysis of randomised controlled trials

Background

Pharmacogenomics (PGx) is a promising tool to realise tailored drug therapy for depression.

Aims

To investigate the treatment efficacy of PGx for treatment-resistant depression (TRD) compared with treatment as usual.

Methods

A systematic search was conducted in PubMed, Embase, the Cochrane Library, Web of Science and PsycINFO to identify relevant studies published from inception to 15 April 2023. Two-arm randomised controlled trials (RCTs) exploring the efficacy of PGx-guided versus unguided treatment for TRD were included. The risk of bias in the included studies was evaluated using the Cochrane risk of bias assessment tool. The overall quality of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach.

Results

Seven RCTs (n=3003) comparing PGx-guided (n=1492) and unguided (n=1511) groups were identified and analysed. PGx-guided treatment was superior to treatment as usual in response (relative risk (RR)=1.31; 95% confidence interval (95% CI): 1.15 to 1.49; p<0.001) and remission (RR=1.40; 95% CI: 1.09 to 1.80; p=0.009) improvements. Effect sizes for acceptability (RR=0.90; 95% CI: 0.80 to 1.02; p=0.100) and side effect burden (RR=0.58; 95% CI: 0.29 to 1.15; p=0.120) between the two groups were not statistically different. The overall quality of evidence was rated from 'very low' (25%) to 'low' (75%) based on the GRADE criteria.

Conclusions

PGx-guided treatment has shown a small overall effect in improving the response and remission rates for patients with TRD. However, these results should be interpreted cautiously because of the few included studies and the low quality of evidence. Further high-quality clinical trials are warranted to confirm the findings.

PROSPERO registration number

CRD42022340182.

The role of pharmacogenetics in the treatment of major depressive disorder: a critical review

Pharmacological therapy represents one of the essential approaches to treatment of Major Depressive Disorder (MDD). However, currently available antidepressant medications show high rates of first-level treatment non-response, and several attempts are often required to find an effective molecule for a specific patient in clinical practice. In this context, pharmacogenetic analyses could represent a valuable tool to identify appropriate pharmacological treatment quickly and more effectively. However, the usefulness and the practical effectiveness of pharmacogenetic testing currently remains an object of scientific debate. The present narrative and critical review focuses on exploring the available evidence supporting the usefulness of pharmacogenetic testing for the treatment of MDD in clinical practice, highlighting both the points of strength and the limitations of the available studies and of currently used tests. Future research directions and suggestions to improve the quality of available evidence, as well as consideration on the potential use of pharmacogenetic tests in everyday clinical practice are also presented.

Effect of pharmacogenomics testing guiding on clinical outcomes in major depressive disorder: a systematic review and meta-analysis of RCT

BACKGROUND

Pharmacogenomic testing guided treatment have been developed to guide drug selection or conversion in major depressive disorder patients. Whether patients benefit from pharmacogenetic testing remains unclear. We aim to evaluates the effect of pharmacogenomic testing guiding on clinical outcomes of major depressive disorder.

METHODS

Pubmed, Embase, and Cochrane Library of Clinical Trials were searched from inception until August 2022. Key terms included pharmacogenomic and antidepressive. Odds ratios (RR) with 95% confidence intervals (95%CIs) were calculated using fixed-effects model for low or moderate heterogeneity or random-effects model for high heterogeneity.

RESULTS

Eleven studies (5347 patients) were included. Compared with usual group, pharmacogenomic testing guided group was associated with an increased response rate at week 8 (OR 1.32, 95%CI 1.15-1.53, 8 studies, 4328 participants) and week 12 (OR 1.36, 95%CI 1.15-1.62, 4 studies, 2814 participants). Similarly, guided group was associated with an increased rate of remission at week 8 (OR 1.58, 95%CI 1.31-1.92, 8 studies, 3971 participants) and week 12 (OR 2.23, 95%CI 1.23-4.04, 5 studies, 2664 participants). However, no significant differences were found between the two groups in response rate at week 4 (OR 1.12, 95%CI 0.89-1.41, 2 studies, 2261 participants) and week 24 (OR 1.16, 95%CI 0.96-1.41, 2 studies, 2252 participants), and remission rate at week 4 (OR 1.26, 95%CI 0.93-1.72, 2 studies, 2261 participants) and week 24 (OR 1.06, 95%CI 0.83-1.34, 2 studies, 2252 participants). Medication congruence in 30 days was significantly reduced in the pharmacogenomic guided group compared with the usual care group (OR 2.07, 95%CI 1.69-2.54, 3 studies, 2862 participants). We found significant differences between subgroups of target population in response and remission rate.

CONCLUSION

Patients with major depressive disorder may benefit from pharmacogenomic testing guided treatment by achieving target response and remission rates more quickly.

Early Insights From a Pharmacogenomic-Enriched Comprehensive Medication Management Program Implementation in an Adult Employee Population

OBJECTIVES

The aims of the study are to assess adoption of a pharmacogenomic-enriched comprehensive medication management program in a self-insured employer setting and to better understand medication risks that affect employees.

METHODS

Employees were identified to be at high risk of medication mismanagement and were subsequently provided with a program and process to improve their health. DNA testing, a clinical decision support system, and pharmacists were used to identify medication safety and effectiveness issues and to recommend appropriate changes.

RESULTS

A total of 10.6% of the invited employees enrolled in the program. Actionable recommendations were suggested by pharmacists for 85.8% of employees who completed the program, averaging 5.2 recommendations per person.

CONCLUSIONS

Implementation of a PGx + CMM program in a self-insured employer setting is feasible, detects risks in prescription regimens, and offers opportunities to improve medication management and reduce the burden of healthcare expenses.

Real-World Impact of a Pharmacogenomics-Enriched Comprehensive Medication Management Program

The availability of clinical decision support systems (CDSS) and other methods for personalizing medicine now allows evaluation of their real-world impact on healthcare delivery. For example, addressing issues associated with polypharmacy in older patients using pharmacogenomics (PGx) and comprehensive medication management (CMM) is thought to hold great promise for meaningful improvements across the goals of the Quadruple Aim. However, few studies testing these tools at scale, using relevant system-wide metrics, and under real-world conditions, have been published to date. Here, we document a reduction of ~$7000 per patient in direct medical charges (a total of $37 million over 5288 enrollees compared to 22,357 non-enrolled) in Medicare Advantage patients (≥65 years) receiving benefits through a state retirement system over the first 32 months of a voluntary PGx-enriched CMM program. We also observe a positive shift in healthcare resource utilization (HRU) away from acute care services and toward more sustainable and cost-effective primary care options. Together with improvements in medication risk assessment, patient/provider communication via pharmacist-mediated medication action plans (MAP), and the sustained positive trends in HRU, we suggest these results validate the use of a CDSS to unify PGx and CMM to optimize care for this and similar patient populations.

Real-world experience of using combinatorial pharmacogenomic test in children and adolescents with depression and anxiety

OBJECTIVE

To evaluate the real-world impact of using a commercially available combinatorial pharmacogenomic (CPGx) test on medication management and clinical outcomes in children and adolescents treated at a tertiary care psychiatry practice.

METHODS

A retrospective cohort study using our prospectively maintained database of patients undergoing CPGx testing was performed. Only patients with clinical data at the time of ordering CPGx test (pre-baseline), potential medication change visit (baseline) and 8-weeks follow-up (post-baseline) visit were included. Clinical Global Impression (CGI) scores for each visit were calculated. Appropriate statistical analysis, including one-sample t-test, paired t-test and Chi-square test was performed.

RESULTS

Based on the inclusion criteria, 281 (75.9%) of the 370 patients with CPGx testing were included. Their mean age was 15.8 ± 4.5 years (111 females; 39.5%). The average number of medications significantly increased to 2.4 ± 1.2 on the post-baseline visit [t(280) = 8.34, p < 0.001). Medications were added in 123 (43.7%), replaced in 92 (32.7%) patients and remained unchanged in rest. There was no significant association between medication-related adverse effects and psychotropic medication change group (p = 0.27). The study population showed a significant improvement (p < 0.001) in the CGI severity, efficacy, and global improvement indices.

CONCLUSION

In our experience of using CPGx test in a large cohort of children and adolescents during routine clinical practice, three-quarter of them underwent medication change. Additionally, we noted an improvement in clinical outcomes without impacting adverse effects. While the role of clinical judgement in medication changes in our cohort is likely, CPGx may supplement clinical decision making. However, the best use and benefit of CPGx in routine clinical practice needs further investigation.

Gene-drug pairings for antidepressants and antipsychotics: level of evidence and clinical application

Substantial inter-individual discrepancies exist in both therapeutic effectiveness and adverse effects of antidepressant and antipsychotic medications, which can, in part, be explained by genetic variation. Here, we searched the Pharmacogenomics Knowledge Base for gene-antidepressant and gene-antipsychotic pairs with the highest level of evidence. We then extracted and compared the associated prescribing recommendations for these pairs developed by the Clinical Pharmacogenomics Implementation Consortium, the Dutch Pharmacogenetics Working Group or approved product labels in the US, Canada, Europe, and Asia. Finally, we highlight key economical, educational, regulatory, and ethical issues that, if not appropriately considered, can hinder the implementation of these recommendations in clinical practice. Our review indicates that evidence-based guidelines are available to assist with the implementation of pharmacogenetic-guided antidepressant and antipsychotic prescribing, although the maximum impact of these guidelines on patient care will not be realized until key barriers are minimized or eliminated.

Effect of pharmacogenomic testing on pharmacotherapy decision making in patients with symptoms of depression in an interprofessional primary care clinic

BACKGROUND

Variability in individual drug response may delay time to relief of symptoms for various disease states. As pharmacogenomic (PGx) testing becomes more widespread, providers are tasked with determining when and in who PGx testing is most appropriate. The use of PGx testing in patients with depressive symptoms has shown some utility, but how this translates to a general population within a primary care setting has yet to be determined.

OBJECTIVE

The objective of this pilot study was to determine the effect of PGx testing on treatment decisions in patients with depressive symptoms in an interprofessional primary care setting.

METHODS

This was a retrospective observational study in which patients who underwent PGx testing for psychotropic medications between April 2019 and March 2021 at a private interprofessional primary care clinic were identified. Charts were reviewed to determine whether a resultant change was made to the prescribed psychotropic medication regimen based on PGx testing results. The number of antidepressants trialed before and after testing was also reviewed. Data were analyzed using descriptive statistics and t test where appropriate.

RESULTS

A total of 78 patients were included in the study. A total of 42 patients (53.8%) experienced a change to their antidepressant regimen after PGx testing. The most frequent change identified was the addition of another antidepressant (50%). This was followed by switching the antidepressant and then by an increase in dose of the prescribed antidepressant. No difference between the number of antidepressants trialed before and after testing was identified.

CONCLUSION

PGx testing in an interprofessional primary care setting leads to a medication change in most patients in this study. Based on the changes identified, testing may be most useful in those beginning treatment with an antidepressant or in those who experience an inadequate response to their prescribed regimen.

Barriers to clinical adoption of pharmacogenomic testing in psychiatry: a critical analysis

Pharmacogenomics (PGx) is the study of genetic influences on an individual's response to medications. Improvements in the quality and quantity of PGx research over the past two decades have enabled the establishment of commercial markets for PGx tests. Nevertheless, PGx testing has yet to be adopted as a routine practice in clinical care. Accordingly, policy regulating the commercialization and reimbursement of PGx testing is in its infancy. Several papers have been published on the topic of challenges, or 'barriers' to clinical adoption of this healthcare innovation. However, many do not include recent evidence from randomized controlled trials, economic utility studies, and qualitative assessments of stakeholder opinions. The present paper revisits the most cited barriers to adoption of PGx testing: evidence for clinical utility, evidence for economic effectiveness, and stakeholder awareness. We consider these barriers in the context of reviewing PGx literature published over the past two decades and emphasize data from commercial PGx testing companies, since they have published the largest datasets. We conclude with a discussion of existing limitations to PGx testing and recommendations for progress.

Pharmacogenetic Testing in an Academic Psychiatric Clinic: A Retrospective Chart Review

Pharmacogenomic (PGx) testing is being increasingly recognized by clinicians as an essential tool to guide medication decisions for treatment of psychiatric illnesses. Extensive implementation of PGx testing, however, varies by setting and location. In this retrospective study, we reviewed charts from 592 patients diagnosed with a psychiatric disorder at the Loyola University Medical Center, for whom PGx testing was performed. Information collected included demographics at the time of testing, psychiatric diagnosis, medical and psychiatric history and medications prior and after PGx testing. Of the 592 charts analyzed, the most common primary diagnoses were depression (52%) and anxiety (12%). Prior to PGx testing, 72% of patients were prescribed three or more medications, whereas, after testing, only 44% were prescribed three or more medications included in the test panel (p < 0.0001). The most common clinical consideration on the PGx reports was recommendation to reduce dosages (33%). After PGx testing, the proportion of patients taking incongruent medications decreased from 26% to 19% and that of patients taking congruent medications increased from 74% to 81% (p = 0.006). The results from this retrospective data analysis demonstrated a reduction in polypharmacy and an increase in recommendation-congruent medication prescribing resulting from implementation of PGx testing.

Pharmacogenomics Guided Prescription Changes Improved Medication Effectiveness in Patients With Mental Health-Related Disability: A Retrospective Cohort Analyses

Mental health problems are the leading cause of disability in Canadian workers. Medication ineffectiveness is hypothesized to increase the time to return-to-work in these workers. We assessed whether prescription changes based on pharmacogenomics profiling ( Report^®) improved medication effectiveness in patients on mental health-related disability. In this retrospective cohort analyses, we assessed the impact of pharmacogenomic profiling on patient outcomes in 84 Canadian workers who were on a mental health-related disability between May 2018 and May 2019. All patients completed an informed consent form and a standard questionnaire including medical history, medications, disease symptoms, and medication side effects. Licensed pharmacists made recommendations for prescription changes in 83 patients. The main study outcome was medication effectiveness defined on a scale of 0 to 10 (0 being most effective and 10 being most ineffective) based on reported mood toward regular work tasks and medication side effects. We compared the medication effectiveness at baseline and at 3 months after the pharmacogenomics-based prescription changes. This retrospective cohort analyses included 46 patients who completed the follow-up questionnaires. Of them, 54% (n = 25) were females, 67% (n = 31) were Caucasians, and the mean age was 38 years (standard deviation [SD] = 11). The average baseline effectiveness score was 8.39 (SD =1.22). Following the prescription changes, the medication effectiveness scores significantly improved to an average of 2.30 (SD = 1.01) at 3 months of follow-up (effect size r = 0.62, p = <0.001). Pharmacogenomics could help in improving treatment outcomes in patients on mental health-related disability.

Economic evaluation in psychiatric pharmacogenomics: a systematic review

Nowadays, many relevant drug-gene associations have been discovered, but pharmacogenomics (PGx)-guided treatment needs to be cost-effective as well as clinically beneficial to be incorporated into standard health care. To address current challenges, this systematic review provides an update regarding previously published studies, which assessed the cost-effectiveness of PGx testing for the prescription of antidepressants and antipsychotics. From a total of 1159 studies initially identified by literature database querying, and after manual assessment and curation of all of them, a mere 18 studies met our inclusion criteria. Of the 18 studies evaluations, 16 studies (88.89%) drew conclusions in favor of PGx testing, of which 9 (50%) genome-guided interventions were cost-effective and 7 (38.9%) were less costly compared to standard treatment based on cost analysis. More precisely, supportive evidence exists for CYP2D6 and CYP2C19 drug-gene associations and for combinatorial PGx panels, but evidence is limited for many other drug-gene combinations. Amongst the limitations of the field are the unclear explanation of perspective and cost inputs, as well as the underreporting of study design elements, which can influence though the economic evaluation. Overall, the findings of this article demonstrate that although there is growing evidence on the cost-effectiveness of genome-guided interventions in psychiatric diseases, there is still a need for performing additional research on economic evaluations of PGx implementation with an emphasis on psychiatric disorders.

Strategies and settings of clinical pharmacogenetic implementation: a scoping review of pharmacogenetics programs

Pharmacogenetic (PGx) literature has shown beneficial outcomes in safety, efficacy and cost when evidence-based gene-drug decision making is incorporated into clinical practice. PGx programs with successfully implemented clinical services have been published in a variety of settings including academic health centers and community practice. The primary objective was to systematically scope the literature to characterize the current trends, extent, range and nature of clinical PGx programs. Forty articles representing 19 clinical PGx programs were included in analysis. Most programs are in urban, academic institutions. Education, governance and workflow were commonly described while billing/reimbursement and consent were not. This review provides an overview of current PGx models that can be used as a reference for institutions beginning the implementation process.

Toward Personalized Medicine Implementation: Survey of Military Medicine Providers in the Area of Pharmacogenomics

INTRODUCTION

Personalized medicine is the right treatment, to the right patient, at the right dose. Knowledge of genetic predisposition to variable metabolism and distribution of drugs within the body is currently available as pharmacogenomic testing and is one of the pillars of personalized medicine. Pharmacogenomic testing is growing. It has become part of guidelines for dosing on FDA labels and has been used by health care organizations to improve outcomes and reduce adverse events. Additionally, it has been FDA approved for direct-to-consumer purchase and has been cause of concern of patient self-dosing and medication changes. Presumably in the near future, pharmacogenomics will be impressed upon the military health system (MHS) provider from either a top-down, command requested, or from a bottom-up, patient requested, approach. To date, widespread implementation of pharmacogenomic testing does not seem to be established within the MHS. This survey sheds light on the knowledge, exposure, use, comfort, and interest among family medicine providers in the MHS. It compares similar results in other national and international surveys and compares results among a small subset of residents to staff.

MATERIALS AND METHODS

The questions were part of a larger survey conducted by the Clinical Investigations Committee of the Uniformed Services Academy of Family Physicians (USAFP) at the USAFP 2019 annual meeting. The study received approval from the Uniformed Services University Institutional Review Board. Submitted questions were written using multiple choice, fill-in, five-point Likert scale, and best answer. Direct results are reported as well as chi-square statistics for categorical data with statistical significance to attain a P-value of < 0.05.

RESULTS

Among the 532 USAFP-registered conference attendees eligible to complete the survey, 387 attendees responded to the survey, for a response rate of 72.7%. Some results included were a knowledge question in which 37% of respondents answered correctly. Less than half of respondents agreed that they could define pharmacogenomics, and resident respondents were more likely to have received teaching in graduate medical education. Additionally, 12% of providers responded to being exposed to direct-to-consumer results, and 28% of those exposed were influenced to change medications, while 14% were influenced to change medications on multiple occasions. Chi-square comparisons resulted in statistically significant direct relationships to exposure to direct to consumer testing, previous training, and confidence of those that answered the knowledge question correctly.

CONCLUSIONS

This survey establishes a baseline for the possible needs associated with implementation of a pharmacogenomic program, and it argues an actionable level for the use of pharmacogenomics among the patient population within the MHS.

Synthesis of major pharmacogenomics pretest counseling themes: a multisite comparison

The accessibility of pharmacogenomic (PGx) testing has grown substantially over the last decade and with it has arisen a demand for patients to be counseled on the use of these tests. While guidelines exist for the use of PGx results; objective determinants for who should receive PGx testing remain incomplete. PGx clinical services have been created to meet these screening and education needs and significant variability exists between these programs. This article describes the practices of four PGx clinics during pretest counseling sessions. A description of the major tenets of the benefits, limitations and risks of testing are compiled. Additional tools are provided to serve as a foundation for those wishing to begin or expand their own counseling service.

Pharmacogenomics for Primary Care: An Overview

Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.

Review and Consensus on Pharmacogenomic Testing in Psychiatry

The implementation of pharmacogenomic (PGx) testing in psychiatry remains modest, in part due to divergent perceptions of the quality and completeness of the evidence base and diverse perspectives on the clinical utility of PGx testing among psychiatrists and other healthcare providers. Recognizing the current lack of consensus within the field, the International Society of Psychiatric Genetics assembled a group of experts to conduct a narrative synthesis of the PGx literature, prescribing guidelines, and product labels related to psychotropic medications as well as the key considerations and limitations related to the use of PGx testing in psychiatry. The group concluded that to inform medication selection and dosing of several commonly-used antidepressant and antipsychotic medications, current published evidence, prescribing guidelines, and product labels support the use of PGx testing for 2 cytochrome P450 genes (CYP2D6, CYP2C19). In addition, the evidence supports testing for human leukocyte antigen genes when using the mood stabilizers carbamazepine (HLA-A and HLA-B), oxcarbazepine (HLA-B), and phenytoin (CYP2C9, HLA-B). For valproate, screening for variants in certain genes (POLG, OTC, CSP1) is recommended when a mitochondrial disorder or a urea cycle disorder is suspected. Although barriers to implementing PGx testing remain to be fully resolved, the current trajectory of discovery and innovation in the field suggests these barriers will be overcome and testing will become an important tool in psychiatry.

Economic Outcomes Following Combinatorial Pharmacogenomic Testing for Elderly Psychiatric Patients

OBJECTIVE

We compared economic outcomes when elderly patients with neuropsychiatric disorders received psychotropic medications guided by a combinatorial pharmacogenomic (PGx) test.

METHODS

This is a subanalysis of a 1-year prospective assessment of medication cost for patients with neuropsychiatric disorders receiving combinatorial PGx testing. Pharmacy claims were used to compare per member per year (PMPY) medication cost for patients ≥65 and <65 years old when medications were congruent or incongruent with the PGx test. Polypharmacy was also assessed.

RESULTS

Congruent prescribing was associated with savings of US$3497 PMPY (P < .001) for patients ≥65 years and US$2467 PMPY (P < .001) for patients <65, compared to incongruent prescribing. Congruent prescribing in patients ≥65 treated by primary care providers was associated with US$4113 PMPY (P = .026) in savings, while congruent prescribing by psychiatrists was associated with US$120 PMPY (P = .719). Congruent prescribing was also associated with one fewer neuropsychiatric medication for patients ≥65 (P = .070).

CONCLUSION

Congruence with PGx testing was associated with medication cost savings in elderly patients.

Prescription patterns of outpatients and the potential of multiplexed pharmacogenomic testing

BACKGROUND

Pre-emptive pharmacogenomic (PGx) testing is potentially an efficient approach to improve drug safety and efficacy but the target population to test is unclear.

OBJECTIVES

We aim to describe the prescription pattern of PGx drugs among adult medical outpatients.

METHODS

We estimated the 5-year cumulative incidence (CI) for receiving three groups of PGx drugs using competing risks analysis: (i) all PGx drugs, (ii) PGx drugs with guidelines and (iii) PGx drugs with serious clinical effects. Comparisons of CIs were also done by patient characteristics using Gray's test.

RESULTS

The 5-year CIs of receiving any new PGx drug, PGx drug with guidelines and serious clinical effects were 42.6%, 37.3% and 13.7%, respectively. The 5-year CI of receiving any new PGx drug was higher for patients >40 years old (43.6% vs ≤40 years old 36.0%, P < 2.2 × 10^-22 ), Malays and Indians (50.3% and 49.8% vs Chinese 31.1%, P < 2.2 × 10^-22 ), those who attended one of the following four specialties at the index visit compared to other specialties (infectious diseases [46.2% vs 42.6%, P = 2.9 × 10^-4 ], psychiatry [48.3% vs 42.3%, P = 7.4 × 10^-13 ], renal [49.8% vs 40.9%, P < 2.2 × 10^-22 ], and rheumatology and immunology [54.8% vs 41.7%, P < 2.2 × 10^-22 ]) and those prescribed ≥5 drugs at index visit (51.7% vs 0-4 drugs 41.7%, P < 2.2 × 10^-22 ).

CONCLUSIONS

Medical outpatients have a substantial probability of benefiting from pre-emptive PGx testing and this is higher in certain subgroups of patients.

Cost–effectiveness of combinatorial pharmacogenomic testing for depression from the Canadian public payer perspective

Aim: Evaluate the cost–effectiveness of combinatorial pharmacogenomic (PGx) testing, versus treatment as usual (TAU), to guide treatment for patients with depression, from the Canadian public healthcare system perspective. Materials & methods: Clinical and economic data associated with depression were extracted from published literature. Clinical (quality-adjusted life years; QALYs) and economic (incremental cost–effectiveness ratio) outcomes were modeled using combinatorial PGx and TAU treatment strategies across a 5-year time horizon. Results: With the combinatorial PGx strategy to guide treatment, patients were projected to gain 0.14–0.19 QALYs versus TAU. Accounting for test price, combinatorial PGx saved CAD $1,687–$3,056 versus TAU. Incremental cost–effectiveness ratios ranged from -$11,861 to -$16,124/QALY gained. Conclusion: Combinatorial PGx testing was more efficacious and less costly compared with the TAU for depression.

Challenges and Future Prospects of Precision Medicine in Psychiatry

Precision medicine is increasingly recognized as a promising approach to improve disease treatment, taking into consideration the individual clinical and biological characteristics shared by specific subgroups of patients. In specific fields such as oncology and hematology, precision medicine has already started to be implemented in the clinical setting and molecular testing is routinely used to select treatments with higher efficacy and reduced adverse effects. The application of precision medicine in psychiatry is still in its early phases. However, there are already examples of predictive models based on clinical data or combinations of clinical, neuroimaging and biological data. While the power of single clinical predictors would remain inadequate if analyzed only with traditional statistical approaches, these predictors are now increasingly used to impute machine learning models that can have adequate accuracy even in the presence of relatively small sample size. These models have started to be applied to disentangle relevant clinical questions that could lead to a more effective management of psychiatric disorders, such as prediction of response to the mood stabilizer lithium, resistance to antidepressants in major depressive disorder or stratification of the risk and outcome prediction in schizophrenia. In this narrative review, we summarized the most important findings in precision medicine in psychiatry based on studies that constructed machine learning models using clinical, neuroimaging and/or biological data. Limitations and barriers to the implementation of precision psychiatry in the clinical setting, as well as possible solutions and future perspectives, will be presented.

The clinical utility of combinatorial pharmacogenomic testing for patients with depression: a meta-analysis

Aim: To perform a meta-analysis of prospective, two-arm studies examining the clinical utility of using the combinatorial pharmacogenomic test, GeneSight Psychotropic, to inform treatment decisions for patients with major depressive disorder (MDD). Patients & methods: The pooled mean effect of symptom improvement and pooled relative risk ratio (RR) of response and remission were calculated using a random effect model. Results: Overall, 1556 patients were included from four studies, with outcomes evaluated at week 8 or week 10. Patient outcomes were significantly improved for patients with MDD whose care was guided by the combinatorial pharmacogenomic test results compared with unguided care (symptom improvement Δ = 10.08%, 95% CI: 1.67-18.50; p = 0.019; response RR = 1.40, 95% CI: 1.17-1.67; p < 0.001; remission RR = 1.49, 95% CI: 1.17-1.89; p = 0.001). Conclusion: GeneSight Psychotropic guided care improves outcomes among patients with MDD.

Canadian Medication Cost Savings Associated with Combinatorial Pharmacogenomic Guidance for Psychiatric Medications

Objective

To estimate Canadian pharmacy cost savings associated with psychiatric medication prescribing that is guided by combinatorial pharmacogenomic testing in patients switching or augmenting their psychiatric medication.

Methods

Pharmacy claims data from a United States (US) pharmacy benefit manager were analyzed for 1662 patients who recently augmented or switched to a different antidepressant or antipsychotic medication and underwent combinatorial pharmacogenomic testing. Costs of prescription medications were translated to the Canadian healthcare system by matching drug names and doses using the Ontario Drug Benefit Formulary. One-year costs (2017 CAD) were compared between patients whose clinician prescribed antidepressants or antipsychotics that were consistent (congruent) or inconsistent (incongruent) with the combinatorial pharmacogenomic test recommendations.

Results

Patients whose psychiatric medication treatment was congruent with the combinatorial pharmacogenomic test report saved $1061 CAD per member per year (PMPY) on prescription medication costs relative to patients whose medications were incongruent with their test report (p<0.0001). For patients ages <65 and ≥65, prescription medication costs were $979 and $1178 CAD PMPY lower, respectively, for patients who followed the report recommendations (p=0.0004 and p=0.13). Prescription drug fills from the US pharmacy claims were concordant with the Canadian Formulary; 62% of fills matched at both the drug name and dose strength, 81% matched at drug name, and >99% matched at the therapeutic chapter.

Conclusions

Antidepressant and antipsychotic prescribing that was congruent with combinatorial pharmacogenomic test guidance was associated with significant cost savings on Canadian prescription medications according to the Ontario Drug Benefit Formulary.

Estimating the Potential Impact of CYP2C19 and CYP2D6 Genetic Testing on Protocol-Based Care for Depression in Canada and the United States

The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) algorithm is the most recognized protocol-based care approach for moderate to severe depression. However, its implementation results in one-third of individuals receiving modest to no symptom remission. One possible explanation is the inter-individual differences in antidepressant metabolism due to CYP2C19 and CYP2D6genetic variation. Here, we aimed to determine the potential benefit of pairing CYP2C19 and CYP2D6testing with the five-step STAR*D algorithm. To estimate the proportion of individuals that could benefit from CYP2C19 and CYP2D6 testing, we simulated the STAR*D algorithm using ethnicity-specific phenotype (e.g., metabolizer status) frequencies published by the Clinical Pharmacogenetics Implementation Consortium and census data from the Canada and the US. We found that up to one-third of the US and Canadian populations being treated for depression could benefit from the addition of CYP2C19and CYP2D6 genetic testing. The potential benefit varied for each step of the algorithm and for each province, territory, and state. CYP2C19 genotyping had the greatest potential impact within the first two steps of the algorithm, while CYP2D6 genotyping had the most notable impact in Steps 3, 4, and 5. Our findings suggest the implementation of CYP2C19and CYP2D6 genetic testing alongside the STAR*D treatment algorithm may improve depression treatment outcomes in Canada and the US.

Preliminary Clinical Investigation of Combinatorial Pharmacogenomic Testing for the Optimized Treatment of Depression: A Randomized Single-Blind Study

This study aims to explore the potential benefits of antidepressant drugs related to metabolic enzyme and drug-targeted genes, identify the optimal treatment of major depression, and provide a reference for individualized medication selection. A prospective randomized single-blind investigation was conducted for 8 weeks. A pharmacogenomic-based interpretive report was provided to the treating physician in the guided group. Patients in this group were informed that their medication selection was directed by DNA testing. In the unguided group, treatment was provided based on the clinical experience of the physician without the guidance of pharmacogenomic testing. Pharmacogenomic-based interpretive report was not provided to these patients until treatment completion. The 17-item Hamilton depression scale (HAMD-17), Hamilton anxiety scale, and treatment emergent symptom scale were used to assess the clinical efficacy and side effects at baseline and after 2, 4, and 8 weeks of treatment. Among the 80 initially enrolled patients with depression, 71 participated in the full data analysis sets and were designated into guided (31) and unguided (40) groups, respectively. No significant difference (P > 0.05) in HAMD-17 total scores, response and remission rates was found between the guided and unguided groups at the end of the treatment. The incidence rate of adverse reaction was 55.56% in guided group and 57.89% in the unguided group. Our study suggested that pharmacogenomic testing might not considerably improve the clinical efficiency and safety for the guided group.

On the utilization of polygenic risk scores for therapeutic targeting

The promise of personalized genomic medicine is that knowledge of a person's gene sequences and activity will facilitate more appropriate medical interventions, particularly drug prescriptions, to reduce the burden of disease. Early successes in oncology and pediatrics have affirmed the power of positive diagnosis and are mostly based on detection of one or a few mutations that drive the specific pathology. However, genetically more complex diseases require the development of polygenic risk scores (PRSs) that have variable accuracy. The rarity of events often means that they have necessarily low precision: many called positives are actually not at risk, and only a fraction of cases are prevented by targeted therapy. In some situations, negative prediction may better define the population at low risk. Here, I review five conditions across a broad spectrum of chronic disease (opioid pain medication, hypertension, type 2 diabetes, major depression, and osteoporotic bone fracture), considering in each case how genetic prediction might be used to target drug prescription. This leads to a call for more research designed to evaluate genetic likelihood of response to therapy and a call for evaluation of PRS, not just in terms of sensitivity and specificity but also with respect to potential clinical efficacy.

Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: A large, patient- and rater-blinded, randomized, controlled study

Current prescribing practices for major depressive disorder (MDD) produce limited treatment success. Although pharmacogenomics may improve outcomes by identifying genetically inappropriate medications, studies to date were limited in scope. Outpatients (N = 1167) diagnosed with MDD and with a patient- or clinician-reported inadequate response to at least one antidepressant were enrolled in the Genomics Used to Improve DEpression Decisions (GUIDED) trial - a rater- and patient-blind randomized controlled trial. Patients were randomized to treatment as usual (TAU) or a pharmacogenomics-guided intervention arm in which clinicians had access to a pharmacogenomic test report to inform medication selections (guided-care). Medications were considered congruent ('use as directed' or 'use with caution' test categories) or incongruent ('use with increased caution and with more frequent monitoring' test category) with test results. Unblinding occurred after week 8. Primary outcome was symptom improvement [change in 17-item Hamilton Depression Rating Scale (HAM-D17)] at week 8; secondary outcomes were response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. At week 8, symptom improvement for guided-care was not significantly different than TAU (27.2% versus 24.4%, p = 0.107); however, improvements in response (26.0% versus 19.9%, p = 0.013) and remission (15.3% versus 10.1%, p = 0.007) were statistically significant. Patients taking incongruent medications prior to baseline who switched to congruent medications by week 8 experienced greater symptom improvement (33.5% versus 21.1%, p = 0.002), response (28.5% versus 16.7%, p = 0.036), and remission (21.5% versus 8.5%, p = 0.007) compared to those remaining incongruent. Pharmacogenomic testing did not significantly improve mean symptoms but did significantly improve response and remission rates for difficult-to-treat depression patients over standard of care (ClinicalTrials.gov NCT02109939).

Use of PHQ-9 and pharmacogenetic testing in clinical practice

BACKGROUND

This project evaluated the clinical use of pharmacogenetic testing in an outpatient psychiatric practice, integrated a standardized measure for assessing depressive symptoms, and captured data regarding treatment efficacy.

LOCAL PROBLEM

According to the Centers for Disease Control and Prevention (2016), more than 10% of all outpatient office visits include a depression-related diagnosis. Patients who require more medication trials to experience remission of depressive symptoms are more likely to relapse in the follow-up period than those who do not (National Institute of Mental Health, 2001).

METHODS AND INTERVENTIONS

Baseline Patient Health Questionnaire-9 (PHQ-9) scores and medication regimens were recorded for 15 adults with major depressive disorder who completed pharmacogenetic testing. Repeat PHQ-9 scores and medication regimens were recorded at follow-up appointments within 6 weeks post-pharmacogenetic testing and compared with baseline data.

RESULTS

The PHQ-9 scores ranged from a 5-point reduction to a 2-point increase in depressive symptoms at follow-up appointment. The PHQ-9 scores were lower at follow-up screening for 14 participants. Six of the 15 participants were on a single medication, with significant drug-gene interactions. Medications with significant drug-gene interactions were eliminated from the regimen for three of the six patients. For the remaining three patients, providers deemed it to be reasonable to continue the medications with significant drug-gene interactions.

CONCLUSIONS

Pharmacogenetic testing is a useful clinical tool for guiding medication selection but does not replace provider judgment. Drug-gene interaction testing results should be considered in addition to patient preference, medication cost, possible side effects, and immediate clinical needs.

Implications of Pharmacogenomics to the Management of IBS

The objectives are to review the role of pharmacogenomics in drug metabolism of medications typically used in patients with irritable bowel syndrome (IBS) focusing predominantly on cytochrome P450 metabolism. Other aims are to provide examples of genetic variation of receptors or intermediary pathways that are targets for IBS drugs and to critically appraise the situations where precision medicine is impacting health in IBS. Pharmacogenomics impacts both pharmacokinetics and pharmacodynamics. Although large clinical trials have not incorporated testing for genetic variations that could impact the efficacy of medications in IBS, there are therapeutic advantages to inclusion of pharmacogenomics testing for individual patients, as has been demonstrated particularly in the treatment with central neuromodulators in psychiatry practice. Clinical practice in IBS is moving in the same direction with the aid of commercially available tests focused on drug metabolism. Specific mechanisms leading to pathophysiology of IBS are still poorly characterized, relative to diseases such as cancer and inflammatory bowel disease, and, therefore, pharmacogenomics related to drug pharmacodynamics is still in its infancy and requires extensive future research. With increased attention to pharmacogenomics affecting drug metabolism, it is anticipated that pharmacogenomics will impact care of IBS.

Horizon Scan Of Clinical Laboratories Offering Pharmacogenetic Testing

Pharmacogenetic (PGx) testing involves the analysis of genes known to affect response to medications. The field has been projected as a leading application of personalized or precision medicine, but the use of PGx tests has been stymied, in part, by the lack of clinical evidence of utility and reported low provider awareness. Another factor is the availability of testing. The range and types of PGx tests available have not been assessed to date. In the period September 2017-January 2018 we analyzed the numbers and types of PGx tests offered by clinical testing laboratories in the US. Of the 111 such labs that we identified, we confirmed that 76 offered PGx testing services. Of these, 31 offered only tests for single genes; 30 offered only tests for multiple genes; and 15 offered both types of tests. Collectively, 45 laboratories offered 114 multigene panel tests covering 295 genes. The majority of these tests did not have any clinical guidelines. PGx tests vary in type and makeup, which presents challenges in appropriate test evaluation and selection for providers, insurers, health systems, and patients alike.

Pharmacogenetic tests and depressive symptom remission: a meta-analysis of randomized controlled trials

Aim: To conducted a systematic review and meta-analysis of prospective, randomized controlled trials (RCTs) that examined pharmacogenetic-guided decision support tools (DSTs) relevant to depressive symptom remission in major depressive disorder (MDD). Patients & methods: Random-effects meta-analysis was performed on RCTs that examined the effect of DSTs on remission rates in MDD. RCT quality was assessed using the Cochrane Collaboration Criteria. Results & conclusion: A total of 1737 eligible subjects from five RCTs were examined. Individuals receiving pharmacogenetic-guided DST therapy (n = 887) were 1.71 (95% CI: 1.17–2.48; p = 0.005) times more likely to achieve symptom remission relative to individuals who received treatment as usual (n = 850). Pharmacogenetic-guided DSTs might improve symptom remission among those with MDD.

Use of combinatorial pharmacogenomic guidance in treating psychiatric disorders

Aim: To evaluate payer costs associated with treating psychiatric disorders utilizing a combinatorial pharmacogenomics test versus treatment-as-usual (TAU). Patients & methods: Administrative claims data were analyzed from health plan members whose treatment was guided by GeneSight® Psychotropic testing (CPGx® cohort) and those who received TAU (TAU cohort). Reimbursed costs were calculated over the 12-month pre-index and post-index event periods. Results: 205 CPGx and 478 TAU members were included. Post-index cost savings (US$5505) drove a per-member-per-month savings of US$0.07. Disease-specific analyses resulted in similar savings. Conclusion: Use of CPGx yielded reduced spending for a commercial health plan across the patient population with psychiatric disorders, as well as among high-cost subpopulations.

Combinatorial pharmacogenomics and improved patient outcomes in depression: Treatment by primary care physicians or psychiatrists

Failed medication trials are common in the treatment of major depressive disorder (MDD); however, the use of combinatorial pharmacogenomics to guide medication selection has been previously associated with improved outcomes in the psychiatric care setting. The utility of combinatorial pharmacogenomics in patients with MDD in primary care and psychiatric care settings was evaluated here. Patients enrolled in a naturalistic, open-label, prospective study [Individualized Medicine: Pharmacogenetics Assessment and Clinical Treatment (IMPACT)] with MDD were evaluated (N = 1871). Pharmacogenomic testing was performed for all patients and medications were categorized based on gene-drug interactions. Beck's Depression Inventory (BDI) was evaluated at baseline and follow-up (weeks 8-12). Symptom improvement (percent decrease in BDI), response (≥50% decrease in BDI), and remission (BDI≤10) at follow-up were evaluated according to provider type and whether medications were genetically congruent (little/no gene-drug interactions). There was a 27.9% reduction in depression symptoms at follow-up, as well as response and remission rates of 25.7% and 15.2%, respectively. Outcomes were significantly better among patients treated by primary care providers versus psychiatrists (symptom improvement 31.7% versus 24.9%, p < 0.01; response rate 30.1% versus 22.3%, p < 0.01; remission rate 19.5% versus 12.0%, p < 0.01). There was a 31% relative improvement in response rate among patients taking congruent versus incongruent medications, with slightly higher congruence among primary care providers (87.6%) versus psychiatrists (85.2%). Following combinatorial pharmacogenomic testing, outcomes were significantly improved among patients treated by primary care providers compared to psychiatrists, which supports the use of pharmacogenomics in broader treatment settings.

Genotype, phenotype, and medication recommendation agreement among commercial pharmacogenetic-based decision support tools

The degree of agreement between four commercial pharmacogenetic-based decision support tools (DSTs) was examined in five outpatients with major depressive disorder and at least two previous antidepressant failures. Comparisons were made across seven pharmacokinetic (CYP1A2, CYP2B6, CYP2C19, CYP2C9, CYP2D6, CYP3A4, and UGT2B15) and seven pharmacodynamic (BDNF, COMT, HLA-A, HTR2A, HTR2C, OPRM1, and SLC6A4) genes that were included on ≥2 of the four DST testing panels. Among these overlapping genes, genotype (33-100%) and predicted phenotype (20-100%) agreement varied substantially. Medication recommendation agreement was the greatest for mood stabilizers (84%), followed by antidepressants (56%), anxiolytics/hypnotics (56%), and antipsychotics (55%). Approximately one-quarter (26%) of all medication recommendations were jointly flagged by two or more DSTs as "actionable" but 19% of these recommendations provided conflicting advice (e.g., dosing) for the same medication.The level of disagreement in medication recommendations across the pharmacogenetic DSTs indicates that these tests cannot be assumed to be equivalent or interchangeable. Additional efforts to standardize genetic-based phenotyping and to develop medication guidelines are warranted.