Reimbursement of pharmacogenetic tests at a tertiary academic medical center in the United States

Implementation of Integrated Clinical Pharmacogenomics Testing at an Academic Medical Center

BACKGROUND

Pharmacogenomics has demonstrated benefits for clinical care, including a reduction in adverse events and cost savings. However, barriers in expanded implementation of pharmacogenomics testing include prolonged turnaround times and integration of results into the electronic health record with clinical decision support. A clinical workflow was developed and implemented to facilitate in-house result generation and incorporation into the electronic health record at a large academic medical center.

METHODS

An 11-gene actionable pharmacogenomics panel was developed and validated using a QuantStudio 12K Flex platform. Allelic results were exported to a custom driver and rules engine, and result messages, which included a diplotype and predicted metabolic phenotype, were sent to the electronic health record; an electronic consultation (eConsult) service was integrated into the workflow. Postimplementation monitoring was performed to evaluate the frequency of actionable results and turnaround times.

RESULTS

The actionable pharmacogenomics panel covered 39 alleles across 11 genes. Metabolic phenotypes were resulted alongside gene diplotypes, and clinician-facing phenotype summaries (Genomic Indicators) were presented in the electronic health record. Postimplementation, 8 clinical areas have utilized pharmacogenomics testing, with 56% of orders occurring in the outpatient setting; 22.1% of requests included at least one actionable pharmacogene, and 67% of orders were associated with a pre- or postresult electronic consultation. Mean turnaround time from sample collection to result was 4.6 days.

CONCLUSIONS

A pharmacogenomics pipeline was successfully operationalized at a quaternary academic medical center, with direct integration of results into the electronic health record, clinical decision support, and eConsult services.

Genotype-driven asthma prescribing of inhaled corticosteroids and long-acting β2-agonist: A cost-effectiveness analysis

INTRODUCTION

Predicting response to inhaled corticosteroids (ICSs) + long-acting β2-agonist (LABA) by previously detecting the presence of Arg16Gly ADRB2 genotype is a strategy that could reduce and optimize the management of asthmatic patients. There is a need for economic evaluations to facilitate the implementation of such tests. This research aims to evaluate the cost-effectiveness of Arg16Gly ADRB2 screening in children with asthma in Colombia.

METHODS

From the perspective of a third-party payer, we conducted a cost-effectiveness analysis to determine the cost and quality-adjusted life-years (QALYs) of genotype-driven asthma prescribing based on the Arg16Gly ADRB2 genotype versus current treatment based on no genetic testing. Using four state-transition models, we estimate cost and QALYs employing micro-simulation modeling with a time horizon of 10 years and a cycle length of 1 week. Cost-effectiveness was assessed at a willingness-to-pay (WTP) value of US$5180.

RESULTS

The mean incremental cost of strategy genetic testing versus no genetic testing is US$ -6809. The mean incremental benefit of strategy genetic testing is 16 QALYs. The incremental net monetary benefit of strategic genetic testing versus no genetic testing is US$ 88,893. Genetic testing is the strategy with the highest expected net benefit. The outcomes derived from our primary analysis remained robust when subjected to variations in all underlying assumptions and parameter values.

CONCLUSION

Genetic testing of Arg16Gly ADRB2 is a cost-effective strategy to address asthma management in asthmatic children requiring ICS+LABA. This result should encourage the generation of more evidence and the incorporation of such evidence into clinical practice guidelines for pediatric asthma.

CYP2C19 Genetic Testing for Oral P2Y12 Inhibitor Therapy: A Scientific Statement From the American Heart Association

There is significant variability in the efficacy and safety of oral P2Y12 inhibitors, which are used to prevent ischemic outcomes in common diseases such as coronary and peripheral arterial disease and stroke. Clopidogrel, a prodrug, is the most used oral P2Y12 inhibitor and is activated primarily after being metabolized by a highly polymorphic hepatic cytochrome CYP2C219 enzyme. Loss-of-function genetic variants in CYP2C219 are common, can result in decreased active metabolite levels and increased on-treatment platelet aggregation, and are associated with increased ischemic events on clopidogrel therapy. Such patients can be identified by CYP2C19 genetic testing and can be treated with alternative therapy. Conversely, universal use of potent oral P2Y12 inhibitors such as ticagrelor or prasugrel, which are not dependent on CYP2C19 for activation, has been recommended but can result in increased bleeding. Recent clinical trials and meta-analyses have demonstrated that a precision medicine approach in which loss-of-function carriers are prescribed ticagrelor or prasugrel and noncarriers are prescribed clopidogrel results in reducing ischemic events without increasing bleeding risk. The evidence to date supports CYP2C19 genetic testing before oral P2Y12 inhibitors are prescribed in patients with acute coronary syndromes or percutaneous coronary intervention. Clinical implementation of such genetic testing will depend on among multiple factors: rapid availability of results or adoption of the concept of performing preemptive genetic testing, provision of easy-to-understand results with therapeutic recommendations, and seamless integration in the electronic health record.

Strategies for DPYD testing prior to fluoropyrimidine chemotherapy in the US

PURPOSE

Patients with dihydropyrimidine dehydrogenase (DPD) deficiency are at high risk for severe and fatal toxicity from fluoropyrimidine (FP) chemotherapy. Pre-treatment DPYD testing is standard of care in many countries, but not the United States (US). This survey assessed pre-treatment DPYD testing approaches in the US to identify best practices for broader adoption.

METHODS

From August to October 2023, a 22-item QualtricsXM survey was sent to institutions and clinicians known to conduct pre-treatment DPYD testing and broadly distributed through relevant organizations and social networks. Responses were analyzed using descriptive analysis.

RESULTS

Responses from 24 unique US sites that have implemented pre-treatment DPYD testing or have a detailed implementation plan in place were analyzed. Only 33% of sites ordered DPYD testing for all FP-treated patients; at the remaining sites, patients were tested depending on disease characteristics or clinician preference. Almost 50% of sites depend on individual clinicians to remember to order testing without the assistance of electronic alerts or workflow reminders. DPYD testing was most often conducted by commercial laboratories that tested for at least the four or five DPYD variants considered clinically actionable. Approximately 90% of sites reported receiving results within 10 days of ordering.

CONCLUSION

Implementing DPYD testing into routine clinical practice is feasible and requires a coordinated effort among the healthcare team. These results will be used to develop best practices for the clinical adoption of DPYD testing to prevent severe and fatal toxicity in cancer patients receiving FP chemotherapy.

Estimating preferences and willingness to pay for pharmacogenetic testing in populations who are medically underserved: a discrete choice experiment

Background: The implementation of pharmacogenetic (PGx) testing may contribute to health disparities if access to testing is inequitable, as medically underserved patients are prescribed higher rates of drugs with PGx guidelines and often experience the benefits of emerging health technologies last. Limited research has evaluated potential implementation of PGx testing in populations who are medically underserved and none have evaluated their preferences regarding PGx test characteristics and cost. Our study endeavored to assess the willingness to pay for PGx testing and key PGx test preferences in a nationwide cohort of medically underserved respondents. Methods: A survey was developed to assess willingness to pay and preferences for PGx testing through a discrete choice experiment (DCE). Five attributes of PGx tests were included in the DCE: doctor recommendation, wait time, number of actionable results, benefit of the test (avoid a side effect or address a health problem), and out-of-pocket cost. A convenience sample of U.S. adults with an average yearly household income of $42,000 or less was collected utilizing an online survey fielded by Qualtrics Research Services (Provo, UT). For the DCE analysis, conditional logit and mixed-logit regression models were utilized to determine relative utility of attributes and levels, conditional relative importance for each attribute, and marginal willingness to pay. Results: Respondents completed the survey with an 83.1% response completion rate. Following quality control procedures, 1,060 respondents were included in the final nationwide cohort. Approximately, 82% of respondents were willing to pay less than $100 for PGx testing, and a strong price ceiling was identified at $200. Out-of-pocket cost was the attribute identified as having the greatest relative importance on choice, while wait time had the lowest importance. Greater utility was observed if the PGx test was doctor recommended, had a higher number of actionable results, and resolved major or minor health problems compared with avoiding side effects. Conclusion: This first-of-its-kind study provides important insights into the willingness to pay for PGx testing and PGx test preferences of a large medically underserved population. Applying these findings can potentially lead to improvements in the successful implementation of PGx testing in this population.

Next-generation sequencing in pharmacogenomics - fit for clinical decision support?

INTRODUCTION

The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial.

AREAS COVERED

We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing.

EXPERT OPINION

While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.

Interrogating Pharmacogenetics Using Next-Generation Sequencing

BACKGROUND

Pharmacogenetics or pharmacogenomics (PGx) is the study of the role of inherited or acquired sequence change in drug response. With the rapid evolution of molecular techniques, bioinformatic tools, and increased throughput of functional genomic studies, the discovery of PGx associations and clinical implementation of PGx test results have now moved beyond a handful variants in single pharmacogenes and multi-gene panels that interrogate a few pharmacogenes to whole-exome and whole-genome scales. Although some laboratories have adopted next-generation sequencing (NGS) as a testing platform for PGx and other molecular tests, most clinical laboratories that offer PGx tests still use targeted genotyping approaches.

CONTENT

This article discusses primarily the technical considerations for clinical laboratories to develop NGS-based PGx tests including whole-genome and whole-exome sequencing analyses and highlights the challenges and opportunities in test design, content selection, bioinformatic pipeline for PGx allele and diplotype assignment, rare variant classification, reporting, and briefly touches a few additional areas that are important for successful clinical implementation of PGx results.

SUMMARY

The accelerated speed of technology development associated with continuous cost reduction and enhanced ability to interrogate complex genome regions makes it inevitable for most, if not all, clinical laboratories to transition PGx testing to an NGS-based platform in the near future. It is important for laboratories and relevant professional societies to recognize both the potential and limitations of NGS-based PGx profiling, and to work together to develop a standard and consistent practice to maximize the variant or allele detection rate and utility of PGx testing.

Lessons from clinical implementation of a preemptive pharmacogenetic panel as part of a testing pilot program with an employer-sponsored medical plan

Introduction: This manuscript reports on a pilot program focused on implementing pharmacogenetic testing within the framework of an employer-sponsored medical plan at University of Florida (UF) Health. The aim was to understand the challenges associated with program implementation and to gather insights into patient attitudes towards PGx testing. Methods: The pilot program adopted a partially preemptive approach, targeting patients on current prescriptions for medications with relevant gene-drug associations. Patients were contacted via phone or through the MyChart system and offered pharmacogenetic testing with no additional direct costs. Results: Of 244 eligible patients, 110 agreed to participate. However, only 61 returned the mailed DNA collection kits. Among these, 89% had at least one potentially actionable genotype-based phenotype. Post-test follow-up revealed that while the majority viewed the process positively, 71% preferred a consultation with a pharmacogenetic specialist for better understanding of their results. Barriers to implementation ranged from fatigue with the healthcare system to a lack of understanding of the pharmacogenetic testing and concerns about privacy and potential misuse of genetic data. Conclusion: The findings underscore the need for clearer patient education on pharmacogenetic results and suggest the importance of the role of pharmacogenetic-trained pharmacists in delivering this education. They also highlight issues with relying on incomplete or inaccurate medication lists in patients' electronic health record. The implementation revealed less obvious challenges, the understanding of which could be beneficial for the success of future preemptive pharmacogenetic implementation programs. The insights from the pilot program served to bridge the information gap between patients, providers, and pharmacogenetic -specialists, with the ultimate goal of improving patient care.