Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program

Implementation and Evaluation Strategies for Pharmacogenetic Testing in Hospital Settings: A Scoping Review

BACKGROUND

Pharmacogenetic testing in clinical settings has improved the safety and efficacy of drug treatment. There is a growing number of studies evaluating pharmacogenetic implementation and identifying barriers and facilitators. However, no review has focused on bridging the gap between identifying barriers and facilitators of testing and the clinical strategies adopted in response. This review was conducted to understand the implementation and evaluation strategies of pharmacogenetic testing programs.

METHODS

A PRISMA-compliant scoping review was conducted. The included studies discussed pharmacogenetic testing programs implemented in a hospital setting. Quantitative, qualitative, and mixed design methods were included.

RESULTS

A total of 232 of the 7043 articles that described clinical pharmacogenetic programs were included. The most common specialties that described pharmacogenetic implementation were psychiatry (26%) and oncology (16%), although many studies described institutional programs implemented across multiple specialties (19%). Different specialties reported different clinical outcomes, but all reported similar program performance indicators, such as test uptake and the number of times the test recommendations were followed. There were benefits and drawbacks to delivering test results through research personnel, pharmacists, and electronic alerts, but active engagement of physicians was necessary for the incorporation of pharmacogenetic results into clinical decision making.

CONCLUSIONS

Further research is required on the maintenance and sustainability of pharmacogenetic testing initiatives. These findings provide an overview of the implementation and evaluation strategies of different specialties that can be used to improve pharmacogenetic testing.

Development of a Multifaceted Program for Pharmacogenetics Adoption at an Academic Medical Center: Practical Considerations and Lessons Learned

In 2019, Indiana University launched the Precision Health Initiative to enhance the institutional adoption of precision medicine, including pharmacogenetics (PGx) implementation, at university-affiliated practice sites across Indiana. The overarching goal of this PGx implementation program was to facilitate the sustainable adoption of genotype-guided prescribing into routine clinical care. To accomplish this goal, we pursued the following specific objectives: (i) to integrate PGx testing into existing healthcare system processes; (ii) to implement drug-gene pairs with high-level evidence and educate providers and pharmacists on established clinical management recommendations; (iii) to engage key stakeholders, including patients to optimize the return of results for PGx testing; (iv) to reduce health disparities through the targeted inclusion of underrepresented populations; (v) and to track third-party reimbursement. This tutorial details our multifaceted PGx implementation program, including descriptions of our interventions, the critical challenges faced, and the major program successes. By describing our experience, we aim to assist other clinical teams in achieving sustainable PGx implementation in their health systems.

Association of Pharmacogenomic Phenotypes in CYP2D6, CYP2C9, CYP2C19, and CYP3A5 on Polypharmacy in Veterans

The Department of Veterans Affairs (VA) utilizes a pharmacogenomic (PGx) program that analyzes specific "pharmacogenes." This study evaluates the effect that pharmacogenes may have on prevalence of polypharmacy. This retrospective cohort study included patients with VA prescriptions who underwent PGx testing. We quantified prescriptions active or recently expired at the time of PGx testing. We constructed two co-primary polypharmacy (≥10 medications) end points: (i) based on all medications and (ii) requiring that at least one medication was affected by a pharmacogene of interest. Pharmacogenes and actionable phenotypes of interest included poor and ultrarapid metabolizers for CYP2D6, CYP2C9, and CYP2C19 and intermediate and normal metabolizers for CYP3A5. Patients were classified as having 0, 1, and 2+ total phenotypes across all genes. Of the 15,144 patients screened, 13,116 met eligibility criteria. Across phenotype cohorts, there was no significant association with polypharmacy using all medications, number of total medications, or number of medications affected by phenotypes. However, there was a significant difference in patients with polypharmacy prescribed ≥1 medication impacted by PGx across phenotype groups: 2,514/4,949 (51%), 1,349/2,595 (52%), 204/350 (58%) (P = 0.03, OR 1.31, 95% CI 1.02-1.67). The median number of medications affected by PGx phenotypes with ≥1 PGx-impacted medication across phenotype groups was a median of 0 (IQR 0, 0), 0 (IQR 0, 0), and 1 (IQR 0, 1) (P < 0.001). In patients prescribed ≥1 medication impacted by PGx, those with more actionable pharmacogenomic phenotypes were more likely to meet polypharmacy criteria.

Aging precisely: Precision medicine through the lens of an older adult

Precision medicine presents an opportunity to use novel, data-driven strategies to improve patient care. The field of precision medicine has undergone many advancements over the past few years. It has moved beyond incorporation of individualized genetic risk into medical decision-making to include multiple other factors such as unique social, demographic, behavioral, and clinical characteristics. Geriatric medicine stands to benefit heavily from the integration of precision medicine into its standard practices. Older adults, compared with other populations, have high clinical and biological heterogeneity that can alter the risks and benefits of different approaches to patient care. These factors have not been routinely considered previously by geriatricians. Yet, geriatricians' ability to address older adults' baseline heterogeneity is increasingly recognized as a cornerstone of delivering quality care in a geriatric medical practice. Given the shared focus of individualized decision-making, precision medicine is a natural fit for geriatric medicine. This manuscript provides, via cases and discussion, examples that illustrate how precision medicine can improve the care of our older patients today. We will share specific and existing tools and evidence, and review the existing multilevel barriers to further incorporate and implement these tools into clinical practice. We propose methods to address these barriers and to help realize the full potential of precision medicine for the care of older adults. We conclude with a brief discussion of potential future directions of research of precision medicine in the care of older adults.

Detection accuracy and clinical applications of DP-TOF mass spectrometry

OBJECTIVE

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently used in clinical microbiology laboratories. This study aimed to determine whether dual-polarity time-of-flight mass spectrometry (DP-TOF MS) could be applied to clinical nucleotide detection.

METHODS

This prospective study included 40 healthy individuals and 110 patients diagnosed with cardiovascular diseases. We used DP-TOF MS and Sanger sequencing to evaluate 17 loci across 11 genes associated with cardiovascular drug responses. In addition, we used DP-TOF MS to test 998 retrospectively collected clinical DNA samples with known results.

RESULTS

A, T, and G nucleotide detection by DP-TOF MS and Sanger sequencing revealed 100% concordance, whereas the C nucleotide concordance was 99.86%. Genotyping based on the results of the two methods showed 99.96% concordance. Regarding clinical applications, DP-TOF MS yielded a 99.91% concordance rate for known loci. The minimum detection limit for DNA was 0.4 ng; the inter-assay and intra-assay precision rates were both 100%. Anti-interference analysis showed that aerosol contamination greater than 1013 copies/µL in the laboratory environment could influence the results of DP-TOF MS.

CONCLUSIONS

The DP-TOF MS platform displayed good detection performance, as demonstrated by its 99.96% concordance rate with Sanger sequencing. Thus, it may be applied to clinical nucleotide detection.

Workforce readiness for pharmacogenomics and key elements for sustainment within the Veterans Health Administration

Aim: Understanding barriers and facilitators to pharmacogenomics (PGx) implementation and how to structure a clinical program with the Veterans Health Administration (VA). Materials & methods: Healthcare provider (HCP) survey at 20 VA facilities assessing PGx knowledge/acceptance and qualitative interviews to understand how best to design and sustain a national program. Results: 186 (12% response rate) surveyed believed PGx informs drug efficacy (74.7%) and adverse events (71.0%). Low confidence in knowledge (43.0%) and ability to implement (35.4-43.5%). 23 (60.5% response rate) interviewees supported a nationally program to oversee VA education, consultation and IT resources. Prescribing HCPs should be directing local activities. Conclusion: HCPs recognize PGx value but are not prepared to implement. Healthcare systems should build system-wide programs for implementation education and support.

Patient Perspectives of Barriers and Facilitators for the Uptake of Pharmacogenomic Testing in Veterans Affairs' Pharmacogenomic Testing for the Veterans (PHASER) Program

We applied implementation science frameworks to identify barriers and facilitators to veterans' acceptance of pharmacogenomic testing (PGx), which was made available as a part of clinical care at 25 VA medical centers. We conducted 30 min interviews with veterans who accepted (n = 14), declined (n = 9), or were contemplating (n = 8) PGx testing. Six team members coded one transcript from each participant group to develop the codebook and finalize definitions. Three team members coded the remaining 28 transcripts and met regularly with the larger team to reach a consensus. The coders generated a matrix of implementation constructs by testing status to identify the similarities and differences between accepters, decliners, and contemplators. All groups understood the PGx testing procedures and possible benefits. In the decision-making, accepters prioritized the potential health benefits of PGx testing, such as reducing side effects or the number of medications. In contrast, decliners prioritized the possibilities of data breach or the negative impact on healthcare insurance or Veterans Affairs benefits. Contemplators desired to speak to a provider to learn more before making a decision. Efforts to improve the clarity of data security and the impact on benefits may improve veterans' abilities to make more informed decisions about whether to undergo PGx testing.

Veterans Health Administration: Implementation of pharmacogenomic clinical decision support with statin medications and the SLCO1B1 gene as an exemplar

PURPOSE

To describe the implementation of clinical decision support tools for alerting prescribers of actionable drug-gene interactions in the Veterans Health Administration (VHA).

SUMMARY

Drug-gene interactions have been the focus of clinicians for years. Interactions between SCLO1B1 genotype and statin medications are of particular interest as these can inform risk for statin-associated muscle symptoms (SAMS). VHA identified approximately 500,000 new users of statin medications prescribed in VHA in fiscal year 2021, some of whom could benefit from pharmacogenomic testing for the SCLO1B1 gene. In 2019, VHA implemented the Pharmacogenomic Testing for Veterans (PHASER) program to offer panel-based, preemptive pharmacogenomic testing and interpretation. The PHASER panel includes SLCO1B1, and VHA utilized Clinical Pharmacogenomics Implementation Consortium statin guidelines to build its clinical decision support tools. The program's overarching goal is to reduce the risk of adverse drug reactions such as SAMS and improve medication efficacy by alerting practitioners of actionable drug-gene interactions. We describe the development and implementation of decision support for the SLCO1B1 gene as an example of the approach being used for the nearly 40 drug-gene interactions screened for by the panel.

CONCLUSION

The VHA PHASER program identifies and addresses drug-gene interactions as an application of precision medicine to reduce veterans' risks for adverse events. The PHASER program's implementation of statin pharmacogenomics utilizes a patient's SCLO1B1 phenotype to alert providers of the risk for SAMS with the statin being prescribed and how to lower that risk through a lower dose or alternative statin selection. The PHASER program may help reduce the number of veterans who experience SAMS and may improve their adherence to statin medications.

Prescription medications with actionable pharmacogenomic recommendations in Veterans Health Administration patients

Aim: To evaluate the prevalence of medications with actionable pharmacogenomic (PGx) safety and efficacy recommendations in patients receiving care from the Veterans Health Administration. Materials & methods: Outpatient prescription data from 2011 to 2021 and any documented adverse drug reactions (ADRs) were reviewed for those who received PGx testing at one Veterans Administration location between November 2019 and October 2021. Results: Among the reviewed prescriptions, 381 (32.8%) were associated with an actionable recommendation based on the Clinical Pharmacogenetics Implementation Consortium (CPIC) prescribing guidelines, with 205 (17.7%) for efficacy concerns and 176 (15.2%) for safety concerns. Among those with a documented ADR for a PGx-impacted medication, 39.1% had PGx results that aligned with CPIC recommendations. Conclusion: Medications with actionable PGx recommendations for safety and efficacy concerns are received with similar frequency, and most patients who have undergone PGx testing at the Phoenix Veterans Administration have received medications that may be impacted by PGx testing.

Progress toward Health System Readiness for Genome-Based Testing in Canada

(1) Background: Genomic medicine harbors the real potential to improve the health and healthcare journey of patients, care provider experiences, and improve the health system efficiency-even reducing healthcare costs. There is expected to be an exponential growth in medically necessary new genome-based tests and test approaches in the coming years. Testing can also create scientific research and commercial opportunities beyond healthcare decision making. The purpose of this research is to generate a better understanding of Canada's state of readiness for genomic medicine, and to provide some insights for other healthcare systems. (2) Methods: A mixed-methods approach of a review of the literature and key informant interviews with a purposive sample of experts was used. The health system readiness was assessed using a previously published set of conditions. (3) Results: Canada has created some of the established conditions, but further action needs to be taken to improve the state of readiness for genome-based medicine. The important gaps to be filled are the need for linked information systems and data integration; evaluative processes that are timely and transparent; navigational tools for care providers; dedicated funding to facilitate rapid onboarding and support test development and proficiency testing; and broader engagement with innovation stakeholders beyond care providers and patients. These findings highlight the role of the organizational context, social influence, and other factors that are known to affect the diffusion of innovation within health systems.

PharmVar GeneFocus: SLCO1B1

The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin-associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self-assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator-submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar-developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin-associated musculoskeletal symptoms.

Pharmacogenomics driven decision support prototype with machine learning: A framework for improving patient care

Introduction

A growing number of healthcare providers make complex treatment decisions guided by electronic health record (EHR) software interfaces. Many interfaces integrate multiple sources of data (e.g., labs, pharmacy, diagnoses) successfully, though relatively few have incorporated genetic data.

Method

This study utilizes informatics methods with predictive modeling to create and validate algorithms to enable informed pharmacogenomic decision-making at the point of care in near real-time. The proposed framework integrates EHR and genetic data relevant to the patient's current medications including decision support mechanisms based on predictive modeling. We created a prototype with EHR and linked genetic data from the Department of Veterans Affairs (VA), the largest integrated healthcare system in the US. The EHR data included diagnoses, medication fills, and outpatient clinic visits for 2,600 people with HIV and matched uninfected controls linked to prototypic genetic data (variations in single or multiple positions in the DNA sequence). We then mapped the medications that patients were prescribed to medications defined in the drug-gene interaction mapping of the Clinical Pharmacogenomics Implementation Consortium's (CPIC) level A (i.e., sufficient evidence for at least one prescribing action) guidelines that predict adverse events. CPIC is a National Institute of Health funded group of experts who develop evidence based pharmacogenomic guidelines. Preventable adverse events (PAE) can be defined as a harmful outcome from an intervention that could have been prevented. For this study, we focused on potential PAEs resulting from a medication-gene interaction.

Results

The final model showed AUC scores of 0.972 with an F1 score of 0.97 with genetic data as compared to 0.766 and 0.73 respectively, without genetic data integration.

Discussion

Over 98% of people in the cohort were on at least one medication with CPIC level a guideline in their lifetime. We compared predictive power of machine learning models to detect a PAE between five modeling methods: Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), K Nearest neighbors (KNN), and Decision Tree. We found that XGBoost performed best for the prototype when genetic data was added to the framework and improved prediction of PAE. We compared area under the curve (AUC) between the models in the testing dataset.

Effective and Efficient Delivery of Genome-Based Testing-What Conditions Are Necessary for Health System Readiness?

Health systems internationally must prepare for a future of genetic/genomic testing to inform healthcare decision-making while creating research opportunities. High functioning testing services will require additional considerations and health system conditions beyond traditional diagnostic testing. Based on a literature review of good practices, key informant interviews, and expert discussion, this article attempts to synthesize what conditions are necessary, and what good practice may look like. It is intended to aid policymakers and others designing future systems of genome-based care and care prevention. These conditions include creating communities of practice and healthcare system networks; resource planning; across-region informatics; having a clear entry/exit point for innovation; evaluative function(s); concentrated or coordinated service models; mechanisms for awareness and care navigation; integrating innovation and healthcare delivery functions; and revisiting approaches to financing, education and training, regulation, and data privacy and security. The list of conditions we propose was developed with an emphasis on describing conditions that would be applicable to any healthcare system, regardless of capacity, organizational structure, financing, population characteristics, standardization of care processes, or underlying culture.

Drug-drug-gene interaction risk among opioid users in the U.S. Department of Veterans Affairs

ABSTRACT

Response to analgesic therapy is influenced by several factors including genetics and drug-drug interactions. Pharmacogenetic (PGx) variants in the CYP2D6 gene modify response to opioids by altering drug metabolism. We sought to determine the potential impact of PGx testing on the care of Veterans with noncancer pain prescribed opioids metabolized by CYP2D6 (codeine, hydrocodone, or tramadol). A retrospective analysis was performed within the Veterans Health Administration (VHA) evaluating prescription records for pain medications metabolized by CYP2D6 and interacting drugs from 2012-2017. Among 2,436,654 VHA pharmacy users with at least one opioid prescription, 34% met the definition of chronic use (longer than 90 days with more than 10 prescriptions or 120 days- supply). Opioids were commonly co-prescribed with antidepressants interacting with CYP2D6 (28%). An estimated 21.6% (n=526,905) of these patients are at elevated risk of an undesirable response to their opioid medication based on predicted phenotypes and drug-drug interactions: 3.5% are predicted CYP2D6 ultrarapid metabolizers and at increased risk for toxicity, 5.4% are poor metabolizer at higher risk for nonresponse, and 12.8% are normal or intermediate metabolizers co-prescribed a CYP2D6 inhibitor leading to phenoconversion into poor metabolizer. Despite the high rate of co-prescription of opioids and interacting drugs, CYP2D6 testing was infrequent in the sample (0.02%) and chart review suggest that test results were used to optimize antidepressant treatments rather than pain medications. Using pharmacogenetic testing combined with consideration of phenoconversion may allow for an enhanced precision medicine approach to pain management in Veterans.

Documenting Pharmacogenomic Test Results in Electronic Health Records: Practical Considerations for Primary Care Teams

With increasing patient interest in and access to pharmacogenomic testing, clinicians practicing in primary care are more likely than ever to encounter a patient seeking or presenting with pharmacogenomic test results. Gene-based prescribing recommendations are available to healthcare providers through Food and Drug Administration-approved drug labeling and Clinical Pharmacogenetics Implementation Consortium guidelines. Given the lifelong utility of pharmacogenomic test results to optimize pharmacotherapy for commonly prescribed medications, appropriate documentation of these results in a patient’s electronic health record (EHR) is essential. The current “gold standard” for pharmacogenomics implementation includes entering pharmacogenomic test results into EHRs as discrete results with associated clinical decision support (CDS) alerts that will fire at the point of prescribing, similar to drug allergy alerts. However, such infrastructure is limited to the few institutions that have invested in the resources and personnel to develop and maintain it. For the majority of clinicians who do not practice at an institution with a dedicated clinical pharmacogenomics team and integrated pharmacogenomics CDS in the EHR, this report provides practical tips for documenting pharmacogenomic test results in the problem list and allergy field to maximize the visibility and utility of results over time, especially when such results could prevent the occurrence of serious adverse drug reactions or predict therapeutic failure.

Evaluation of the Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program at initial test sites

Aim: The first Plan-Do-Study-Act cycle for the Veterans Affairs Pharmacogenomic Testing for Veterans pharmacogenomic clinical testing program is described. Materials & methods: Surveys evaluating implementation resources and processes were distributed to implementation teams, providers, laboratory and health informatics staff. Survey responses were mapped to the Consolidated Framework for Implementation Research constructs to identify implementation barriers. The Expert Recommendation for Implementing Change strategies were used to address implementation barriers. Results: Survey response rate was 23-73% across personnel groups at six Veterans Affairs sites. Nine Consolidated Framework for Implementation Research constructs were most salient implementation barriers. Program revisions addressed these barriers using the Expert Recommendation for Implementing Change strategies related to three domains. Conclusion: Beyond providing free pharmacogenomic testing, additional implementation barriers need to be addressed for improved program uptake.

Revisiting Secondary Information Related to Pharmacogenetic Testing

Incidental or secondary findings have been a major part of the discussion of genomic medicine research and clinical applications. For pharmacogenetic (PGx) testing, secondary findings arise due to the pleiotropic effects of pharmacogenes, often related to their endogenous functions. Unlike the guidelines that have been developed for whole exome or genome sequencing applications for management of secondary findings (though slightly different from PGx testing in that these refer to detection of variants in multiple genes, some with clinical significance and actionability), no corresponding guidelines have been developed for PGx clinical laboratories. Nonetheless, patient and provider education will remain key components of any PGx testing program to minimize adverse responses related to secondary findings.

Clinical Utility of Pharmacogenomic Data Collected by a Health-System Biobank to Predict and Prevent Adverse Drug Events

INTRODUCTION

Medication-related harm represents a significant issue for patient safety and quality of care. One strategy to avoid preventable adverse drug events is to utilize patient-specific factors such as pharmacogenomics (PGx) to individualize therapy.

OBJECTIVE

We measured the number of patients enrolled in a health-system biobank with actionable PGx results who received relevant medications and assessed the incidence of adverse drug events (ADEs) that might have been prevented had the PGx results been used to inform prescribing.

METHODS

Patients with actionable PGx results in the following four genes with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines were identified: HLA-A*31:01, HLA-B*15:02, TPMT, and VKORC1. The patients who received interacting medications (carbamazepine, oxcarbazepine, thiopurines, or warfarin) were identified, and electronic health records were reviewed to determine the incidence of potentially preventable ADEs.

RESULTS

Of 36,424 patients with PGx results, 2327 (6.4%) were HLA-A*31:01 positive; 3543 (9.7%) were HLA-B*15:02 positive; 2893 (7.9%) were TPMT intermediate metabolizers; and 4249 (11.7%) were homozygous for the VKORC1 c.1639 G>A variant. Among patients positive for one of the HLA variants who received carbamazepine or oxcarbazepine (n = 92), four (4.3%) experienced a rash that warranted drug discontinuation. Among the TPMT intermediate metabolizers who received a thiopurine (n = 56), 11 (19.6%) experienced severe myelosuppression that warranted drug discontinuation. Among patients homozygous for the VKORC1 c.1639 G>A variant who received warfarin (n = 379), 85 (22.4%) experienced active bleeding and/or international normalized ratio (INR) > 5 that warranted drug discontinuation or dose reduction.

CONCLUSION

Patients with actionable PGx results from a health-system biobank who received relevant medications experienced predictable ADEs. These ADEs may have been prevented if the patients' PGx results were available in the electronic health record with clinical decision support prior to prescribing.