Combinatorial Pharmacogenomic Testing Research Articles

Pharmacogenomic Profiling of Pediatric Patients on Psychotropic Medications in an Emergency Department.

The aim of the study was to evaluate the ability of a combinatorial pharmacogenomic test to predict medication blood levels and relative clinical improvements in a selected pediatric population. This study enrolled patients between ages 3 to 18 years who presented to a pediatric emergency department with acute psychiatric, behavioral, or mental health crisis and/or concerns, and had previously been prescribed psychotropic medications. Patients received combinatorial pharmacogenomic testing with medications categorized according to gene-drug interactions (GDIs); medications with a GDI were considered "incongruent," and medications without a GDI were considered "congruent." Blood levels for escitalopram, fluoxetine, aripiprazole, and clonidine were evaluated according to level of GDI. Relative clinical improvements in response to the prescribed psychotropic medications were measured using a parent-rated Clinical Global Impression of Improvement (CGI-I) assessment, where lower scores corresponded with greater improvement. Of the 100 patients enrolled, 73% reported taking ≥1 incongruent medication. There was no significant difference in CGI-I scores between patients prescribed congruent versus incongruent medications (3.37 vs 3.68, P = 0.343). Among patients who presented for depression or suicidal ideation, those prescribed congruent medications had significantly lower CGI-I scores compared with those taking incongruent medications ( P = 0.036 for depression, P = 0.018 for suicidal ideation). There was a significant association between medication GDI and blood levels for aripiprazole (n = 15, P = 0.01) and escitalopram (n = 10, P = 0.01). Our preliminary findings suggest that combinatorial pharmacogenomic testing can predict medication blood levels and relative outcomes based on medication congruency in children presenting to an emergency department with acute psychiatric/behavioral crises. Additional studies will be needed to confirm these findings.

Clinical utility of combinatorial pharmacogenomic testing in depression: A Canadian patient- and rater-blinded, randomized, controlled trial

The pharmacological treatment of depression consists of stages of trial and error, with less than 40% of patients achieving remission during first medication trial. However, in a large, randomized-controlled trial (RCT) in the U.S. (“GUIDED”), significant improvements in response and remission rates were observed in patients who received treatment guided by combinatorial pharmacogenomic testing, compared to treatment-as-usual (TAU). Here we present results from the Canadian “GAPP-MDD” RCT. This 52-week, 3-arm, multi-center, participant- and rater-blinded RCT evaluated clinical outcomes among patients with depression whose treatment was guided by combinatorial pharmacogenomic testing compared to TAU. The primary outcome was symptom improvement (change in 17-item Hamilton Depression Rating Scale, HAM-D17) at week 8. Secondary outcomes included response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. Numerically, patients in the guided-care arm had greater symptom improvement (27.6% versus 22.7%), response (30.3% versus 22.7%), and remission rates (15.7% versus 8.3%) compared to TAU, although these differences were not statistically significant. Given that the GAPP-MDD trial was ultimately underpowered to detect statistically significant differences in patient outcomes, it was assessed in parallel with the larger GUIDED RCT. We observed that relative improvements in response and remission rates were consistent between the GAPP-MDD (33.0% response, 89.0% remission) and GUIDED (31.0% response, 51.0% remission) trials. Together with GUIDED, the results from the GAPP-MDD trial indicate that combinatorial pharmacogenomic testing can be an effective tool to help guide depression treatment in the context of the Canadian healthcare setting (ClinicalTrials.gov NCT02466477).

Combinatorial pharmacogenomic algorithm is predictive of sertraline metabolism in patients with major depressive disorder

Pharmacogenomic testing can be used to guide medication selection in patients with major depressive disorder (MDD). Currently, there is no consensus on which gene or genes to consider in medication management. Here, we assessed the clinical validity of the combinatorial pharmacogenomic algorithm to predict sertraline blood levels in a subset of patients enrolled in the Genomics Used to Improve DEpression Decisions (GUIDED) trial. Patients who reported taking sertraline within ≤2 weeks of the screening blood draw were included. All patients received combinatorial pharmacogenomic testing, which included a weighted assessment of individual phenotypes for multiple pharmacokinetic genes relevant for sertraline (CYP2C19, CYP2B6, and CYP3A4). Sertraline blood levels were compared between phenotypes based on: 1) the pharmacokinetic portion of the combinatorial pharmacogenomic algorithm, and 2) individual genes. When evaluated separately, individual genes (for CYP2C19 and CYP2B6) and the combinatorial algorithm were significant predictors of sertraline blood levels. However, in multivariate analyses that included individual genes and the combinatorial pharmacogenomic algorithm, only the combinatorial pharmacogenomic algorithm remained a significant predictor of sertraline blood levels. These findings support the clinical validity of the combinatorial pharmacogenomic algorithm, in that it is a superior predictor of sertraline blood levels compared to individual genes.

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

ObjectiveTo 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. MethodsA 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. ResultsBased 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. ConclusionIn 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.

Pharmacogenomic Testing to Inform Prescribing in Patients with Behavioral and Psychiatric Symptoms of Dementia (BPSD): Results from Two Small, Randomized, Controlled Trials

<h3>Introduction</h3> Behavioral and psychiatric symptoms of dementia (BPSD) occur frequently, representing a significant driver of the total costs of dementia in the US. Although antidepressants and atypical antipsychotics are often used in BPSD, they have limited effectiveness and significant toxicity. As a result, recent initiatives have focused on reducing polypharmacy and psychotropic prescribing in this population. Combinatorial pharmacogenomic testing has demonstrated utility in guiding prescribing for psychotropic medications in patients with depression by identifying medications unlikely to be safe or effective due to significant gene-drug interactions. Here we present data from two small, randomized, controlled trials (RCTs) designed to test the hypothesis that combinatorial pharmacogenomic testing could aid in treatment selection for BPSD. <h3>Methods</h3> The first RCT included residents being treated at the Bayleigh Chance retirement community in Maryland (inpatient RCT). The second RCT included patients from the University of Alabama at Birmingham Memory Disorders Clinic (outpatient RCT). Patients were eligible if they had a diagnosis of dementia with psychotic symptoms and/or behavioral disturbance and their condition was severe enough to trigger a consultation with a physician (inpatient RCT) or their physician was considering starting/changing a psychotropic medication (outpatient RCT). For the outpatient RCT, patients were also required to have a caregiver who spends at least 10 hours a week with them. Informed consent was obtained at the screening visit from patients' legally authorized representatives. The inpatient RCT intended to enroll 50 patients and the outpatient RCT intended to enroll 100 patients. Both studies were stopped early due to slow enrollment. Patients were randomized 1:1 to treatment as usual (TAU) or the combinatorial pharmacogenomic-guided care arm. All patients received combinatorial pharmacogenomic testing (GeneSight, Assurex Health). Variants in multiple pharmacokinetic and pharmacodynamic genes were assessed and a weighted combinatorial algorithm categorized medications according to the level of predicted gene-drug interactions (GDI). For patients in the guided-care arm, physicians had access to the test report at the time of the baseline visit. Physicians were blinded to the test report until after the trial for patients in TAU. Assessments were performed at baseline, week 2 (AEs only, inpatient RCT only), week 4 (outpatient RCT only), week 8, and week 12. The primary outcome was the Neuropsychiatric Inventory (NPI), which assesses the presence and severity of BPSD across 12 domains. The nursing home version (NPI-NH) was used for the inpatient RCT and the NPI questionnaire (NPI-Q) was used for the outpatient RCT. A Mixed Model for Repeated Measures (MMRM) was utilized to evaluate NPI and included treatment, week, treatment-by-week interaction, baseline score, baseline score-by-week interaction as fixed effects. The presence of a condition (i.e. depression) was evaluated as a score >0 for the relevant domain on the NPI. Side effects were evaluated using the SA-EPS and MOSES scale (inpatient RCT) or the FIBSER scale (outpatient RCT). Changes in prescribing relative to a pre-test intended medication plan were evaluated in the outpatient RCT. <h3>Results</h3> A total of 12 patients were enrolled in the inpatient RCT (5 in TAU; 7 in guided-care) and 38 patients were enrolled in the outpatient RCT (19 in TAU; 19 in guided-care). At week 12, there were no significant differences in NPI or side effects between guided-care and TAU in either RCT (Table 1). However, the proportion of outpatients experiencing depression at week 12 was significantly lower in the guided-care arm versus TAU (p=0.0479). In the outpatient RCT, the proportion of patients prescribed at least one medication subject to GDI decreased from 58.8% (pre-test) to 25.0% (week 12) in the guided-care arm (Table 2). In contrast, there was an increase in the proportion of patients in TAU taking medications subject to GDI throughout the trial. A significantly higher proportion of patients in the guided-care arm had a reduction in the number of prescribed psychotropic medications by week 12 compared to TAU (Table 2). <h3>Conclusions</h3> Overall, there were no observed differences in overall neuropsychiatric symptoms or side effects among inpatients or outpatients who received pharmacogenomic-guided care compared to TAU. It should be noted that these studies were stopped early due to slow enrollment and were likely underpowered to detect any differences. However, there was a significant reduction in the proportion of outpatients with depression in the guided care arm, which is consistent with the validated use of combinatorial pharmacogenomic testing among patients with depression. There was also evidence that pharmacogenomic-guided care did inform prescribing, with reduced prescribing of medications subject to GDI and reduced psychotropic medication polypharmacy. <h3>Funding</h3> Myriad Neuroscience (Formerly Assurex Health)

Combinatorial pharmacogenomic test for successful antidepressant treatment of a major depressive disorder

Introduction. The combinatorial pharmacogenomic test has shown the potential to predict antidepressant response, tolerability, selection, and dosage in the treatment of a major depressive disorder. A case of successful management of antidepressant therapy adjustment is reported by using the combinatorial pharmacogenomic test. Case Report. A 53-year old man, severely disabled due to a rare genetic disease, Usher syndrome type 3, was treated with numerous antidepressants. However, episodes of major depression recurred, along with frequent suicidal thoughts. A combinatorial pharmacogenomic test was considered to design a potentially effective antidepressant therapy. Conclusion. According to the results of the combinatorial pharmacogenomic test, the patient constantly received inadequate antidepressant therapy, which did not lead to an improvement of depression due to moderate gene-drug interaction. The patient was prescribed nortriptyline, which proved to be one of the few most adequate according to the test. He showed improvement with subjectively more tolerable depression without suicidal thoughts and episodes of major depression. This case showed that the combinatorial pharmacogenomic testing may contribute to better selection of antidepressant therapy.

Combinatorial Pharmacogenomic Testing Improves Outcomes for Older Adults With Depression.

(Reprinted with permission from Am J Geriatr Psychiatry 2020; 28:933-945).

Clinical validation of combinatorial pharmacogenomic testing and single-gene guidelines in predicting psychotropic medication blood levels and clinical outcomes in patients with depression

We evaluated the clinical validity of a combinatorial pharmacogenomic test and single-gene Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines against patient outcomes and medication blood levels to assess their ability to inform prescribing in major depressive disorder (MDD).This is a secondary analysis of the Genomics Used to Improve DEpression Decisions (GUIDED) randomized-controlled trial, which included patients with a diagnosis of MDD, and ≥1 prior medication failure. The ability to predict increased/decreased medication metabolism was validated against blood levels at screening (adjusted for age, sex, smoking status). The ability of predicted gene-drug interactions (pharmacogenomic test) or therapeutic recommendations (single-gene guidelines) to predict patient outcomes was validated against week 8 outcomes (17-item Hamilton Depression Rating Scale; symptom improvement, response, remission). Analyses were performed for patients taking any eligible medication (outcomes N=1,022, blood levels N=1,034) and the subset taking medications with single-gene guidelines (outcomes N=584, blood levels N=372). The combinatorial pharmacogenomic test was the only significant predictor of patient outcomes. Both the combinatorial pharmacogenomic test and single-gene guidelines were significant predictors of blood levels for all medications when evaluated separately; however, only the combinatorial pharmacogenomic test remained significant when both were included in the multivariate model. There were no substantial differences when all medications were evaluated or for the subset with single-gene guidelines. Overall, this evaluation of clinical validity demonstrates that the combinatorial pharmacogenomic test was a superior predictor of patient outcomes and medication blood levels when compared with guidelines based on individual genes.

Combinatorial Pharmacogenomic Testing Improves Outcomes for Older Adults With Depression

Evaluate the clinical utility of combinatorial pharmacogenomic testing for informing medication selection among older adults who have experienced antidepressant medication failure for major depressive disorder (MDD). Post hoc analysis of data from a blinded, randomized controlled trial comparing two active treatment arms. Psychiatry specialty and primary care clinics across 60 U.S. community and academic sites. Adults age 65 years or older at baseline (n = 206), diagnosed with MDD and inadequate response to at least one medication on the combinatorial pharmacogenomic test report during the current depressive episode. Combinatorial pharmacogenomic testing to inform medication selection (guided-care), compared with treatment as usual (TAU). Mean percent symptom improvement, response rate, and remission rateat week 8, measured using the 17-item Hamilton Depression Rating Scale; medication switching; and comorbidity moderator analysis. At week 8, symptom improvement was not significantly different for guided-care than for TAU (∆ = 8.1%, t = 1.64, df = 187; p = 0.102); however, guided-care showed significantly improved response (∆ = 13.6%, t = 2.16, df = 187; p = 0.032) and remission (∆ = 12.7%, t = 2.49, df = 189; p = 0.014) relative to TAU. By week 8, more than twice as many patients in guided-care than in TAU were on medications predicted to have no gene-drug interactions (χ2 = 19.3, df = 2; p <0.001). Outcomes in the guided-care arm showed consistent improvement through the end of the open-design 24-week trial, indicating durability of the effect. Differences in outcomes between arms were not significantly impacted by comorbidities. Combinatorial pharmacogenomic test-informed medication selection improved outcomes over TAU among older adults with depression.

Combinatorial Pharmacogenomic Algorithm is Predictive of Citalopram and Escitalopram Metabolism in Patients with Major Depressive Disorder

Pharmacogenomic tests used to guide clinical treatment for major depressive disorder (MDD) must be thoroughly validated. One important assessment of validity is the ability to predict medication blood levels, which reflect altered metabolism. Historically, the metabolic impact of individual genes has been evaluated; however, we now know that multiple genes are often involved in medication metabolism. Here, we evaluated the ability of individual pharmacokinetic genes (CYP2C19, CYP2D6, CYP3A4) and a combinatorial pharmacogenomic test (GeneSight Psychotropic®; weighted assessment of all three genes) to predict citalopram/escitalopram blood levels in patients with MDD. Patients from the Genomics Used to Improve DEpression Decisions (GUIDED) trial who were taking citalopram/escitalopram at screening and had available blood level data were included (N=191). In multivariate analysis of the individual genes and combinatorial pharmacogenomic test separately (adjusted for age, smoking status), the F statistic for the combinatorial pharmacogenomic test was 1.7 to 2.9-times higher than the individual genes, showing that it explained more variance in citalopram/escitalopram blood levels. In multivariate analysis of the individual genes and combinatorial pharmacogenomic test together, only the combinatorial pharmacogenomic test remained significant. Overall, this demonstrates that the combinatorial pharmacogenomic test was a superior predictor of citalopram/escitalopram blood levels compared to individual genes.

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.

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.

COMBINATORIAL PHARMACOGENETIC TESTING IMPROVES RESPONSE AND REMISSION FOR PATIENTS OVER 65 WITH DEPRESSION WHO HAVE FAILED ONE MEDICATION TRIAL

Introduction Six million people in the U.S. experience depression after age 65. Major depressive disorder (MDD) in later life is associated with longer length of illness, increased number of MDD episodes, and a greater risk of comorbidities. Challenges facing clinicians when making prescription decisions for older adults include increased drug-drug interactions, lower adherence, and higher rates of adverse events. Medication trials for MDD can be difficult to navigate in older patients due to increased polypharmacy for multiple conditions. As the aging population grows, the demand for data-driven tools to optimize medication prescribing for older patients with MDD is gaining momentum. Combinatorial pharmacogenomic (PGx) testing may improve and personalize medication prescribing for older patients by identifying medications that have patient-specific adverse gene-drug interactions. Methods The GUIDED study was a blinded, randomized controlled trial which sought to evaluate the use of a combinatorial PGx test in improving outcomes for patients with MDD by guiding medication treatment decisions. Patients were randomized to either the guided-care arm where the combinatorial PGx test result was available to providers to guide treatment decisions or to the treatment as usual (TAU) arm where the test result was not available to providers until after the primary endpoint. Both patients and raters were blinded to the arm until after the completion of the primary endpoint week 8 assessment. The primary endpoint was symptom improvement on the 17-Item Hamilton Depression Rating Scale (HAM-D17). Secondary endpoints included response (50% reduction in HAM-D17 from baseline) and remission (score ≤7 on HAM-D17). In this subanalysis, we evaluated whether patients aged 65 and older had differences in outcomes based on treatment guidance from combinatorial PGx testing. Results In the GUIDED study, 206 patients were 65+ years of age at baseline with a median age of 69; 108 patients in the treatment as usual (TAU) and 98 patients in the guided-care arm (combinatorial PGx test). The mean HAM-D17 score at baseline overall was 19.8 for all patients, 20.2 in the TAU arm and 19.4 in the guided-care arm. The average number of failed medication trials was 3.5 (3.7 in TAU and 3.3 in guided-care). At week 8, there was a 26.7% decrease in HAM-D17 scores in the guided-care arm (n=86) compared to an 18.7% decrease in TAU (n=98). The difference in symptom improvement between arms did not reach statistical significance (p=0.102). Response rate was significantly higher in the guided-care arm at week 8, with 29.6% of patients experiencing response, compared to 16.1% in TAU (p=0.032). The remission rate was also significantly higher in the guided-care arm at week 8 (20.1%), compared to TAU (7.4%, p=0.014). Conclusions Patients who were 65?years or older in the GUIDED trial whose medication treatment was guided by combinatorial PGx testing achieved significantly better response and remission rates compared to TAU. The difference in symptom improvement in this population did not reach statistical significance. Overall, the data presented here support the utility of using combinatorial PGx testing to help guide antidepressant medication selection with a goal to improve outcomes of depression. This research was funded by: Myriad Genetics, Inc.

Economic Outcomes Following Combinatorial Pharmacogenomic Testing for Elderly Psychiatric Patients.

We compared economic outcomes when elderly patients with neuropsychiatric disorders received psychotropic medications guided by a combinatorial pharmacogenomic (PGx) test. 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. 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). Congruence with PGx testing was associated with medication cost savings in elderly patients.

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

ObjectiveTo 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.MethodsPharmacy 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.ResultsPatients 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.ConclusionsAntidepressant 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.

Impact of Pharmacogenomics on Clinical Outcomes for Patients Taking Medications With Gene-Drug Interactions in a Randomized Controlled Trial

The objective of the Genomics Used to Improve DEpression Decisions (GUIDED) trial was to evaluate the utility of pharmacogenomic testing to improve outcomes among patients with major depressive disorder (MDD) who had not responded to at least 1 prior medication trial. The objective of the present analysis was to assess outcomes for the subset of patients expected to benefit from combinatorial pharmacogenomic testing because they were taking medications with predicted gene-drug interactions. Participants (enrolled from April 14, 2014, to February 10, 2017) had an inadequate response to at least 1 psychotropic medication in the current episode of MDD. Patients were randomized to treatment as usual (TAU) or the guided-care arm, in which clinicians had access to a combinatorial pharmacogenomic test report to inform medication selection. Patients and raters were blinded to study arm through week 8. The following outcomes were assessed using the 17-item Hamilton Depre​ssion Rating Scale (HDRS-17): symptom improvement (percent change in HDRS-17 score), response (≥ 50% decrease in HDRS-17 score), and remission (HDRS-17 score ≤ 7). In the GUIDED trial, the primary endpoint of symptom improvement did not reach significance in the intent-to-treat cohort (P = .069). Here, a post hoc analysis of patients who were taking medications subject to gene-drug interactions at baseline as predicted by combinatorial pharmacogenomic testing (N = 912) is presented. Among participants taking medications subject to gene-drug interactions at baseline, outcomes at week 8 were significantly improved for those in the guided-care arm compared to TAU (symptom improvement: 27.1% versus 22.1%, P = .029; response: 27.0% versus 19.0%, P = .008; remission: 18.2% versus 10.7%, P = .003). When patients who switched medications were assessed, all outcomes were significantly improved in the guided-care arm compared to TAU (P = .011 for symptom improvement, P = .011 for response, P = .008 for remission). By identifying and focusing on the patients with predicted gene-drug interactions, use of a combinatorial pharmacogenomic test significantly improved outcomes among patients with MDD who had at least 1 prior medication failure. ClinicalTrials.gov identifier: NCT02109939​.

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.

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.

Does Pharmacogenomic Testing Improve Clinical Outcomes for Major Depressive Disorder? A Systematic Review of Clinical Trials and Cost-Effectiveness Studies.

Pharmacogenomic testing has become scalable and available to the general public. Pharmacogenomics has shown promise for predicting antidepressant response and tolerability in the treatment of major depressive disorder (MDD). In theory, pharmacogenomics can improve clinical outcomes by guiding antidepressant selection and dosing. The current systematic review examines the extant literature to determine the impact of pharmacogenomic testing on clinical outcomes in MDD and assesses its cost-effectiveness. The MEDLINE/PubMed and Google Scholar databases were systematically searched for relevant articles published prior to October 2015. Search terms included various combinations of the following: major depressive disorder (MDD), depression, mental illness, mood disorder, antidepressant, response, remission, outcome, pharmacogenetic, pharmacogenomics, pharmacodynamics, pharmacokinetic, genetic testing, genome wide association study (GWAS), CYP450, personalized medicine, cost-effectiveness, and pharmacoeconomics. Of the 66 records identified from the initial search, relevant clinical studies, written in English, assessing the cost-effectiveness and/or efficacy of pharmacogenomic testing for MDD were included. Each publication was critically examined for relevant data. Two nonrandomized, open-label, 8-week, prospective studies reported overall greater improvement in depressive symptom severity in the group of MDD subjects receiving psychiatric care guided by results of combinatorial pharmacogenomic testing (GeneSight) when compared to the unguided group. One industry-sponsored, randomized, double-blind, 10-week prospective study reported a trend for improved outcomes for the GeneSight-guided group; however, the trend did not reach statistical significance. Another industry-sponsored, randomized, double-blind, 12-week prospective study reported a 2.5-fold increase in remission rates in the CNSDose-guided group (P < .0001). One naturalistic, unblinded, industry-sponsored study showed clinical improvement when pharmacogenomics testing guided prescribing; however, this study lacked a control group. A single cost-effectiveness study concluded that single gene testing was not cost-effective. Conversely, a separate study reported that combinatorial pharmacogenomic testing is cost-effective. A limited number of studies have shown promise for the clinical utility of pharmacogenomic testing; however, cost-effectiveness of pharmacogenomics, as well as demonstration of improved health outcomes, is not yet supported with replicated evidence.

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

PurposeThis study was an analysis based on a previously completed prospective study investigating medication costs of patients with mental illness guided by using the GeneSight proprietary combinatorial pharmacogenomic (PGx) test. The primary objective of this study was to determine potential cost savings of combinatorial PGx testing over the course of 1 year in patients with mental illness treated by primary care providers (PCPs) and psychiatrists who had switched or added a new psychiatric medication after patients failed to respond to monotherapy. The current evaluation details cost savings of treatment decisions congruent and incongruent with the combinatorial PGx test recommendations specific to PCPs and psychiatrists. MethodsThis study was a subanalysis of a 1-year, prospective trial comparing medication costs of 2168 patients undergoing GeneSight testing. Pharmacy claims were provided by a pharmacy benefits manager, comparing medication costs 6 months before combinatorial PGx testing and followed up for 1 year after the testing. This analysis compared congruence and cost savings per patient based on the type of health care provider administering care. FindingsUsing data from a large pharmacy benefits manager, we found that PCPs treat the majority of mental health patients receiving psychotropic medication prescriptions, including treatment-resistant patients. PCPs congruent with combinatorial PGx testing provided the most medication cost savings for payers and patients at $3988 per member per year (P < 0.001). ImplicationsHealth care providers treating patients with mental illness can significantly reduce medication costs by following the combinatorial PGx report recommendations. PCPs, who treat the majority of patients with mental illness, reported a significant reduction in medication costs for both central nervous system and non–central nervous system drugs.