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.

Integrating pharmacogenomic testing into paired germline and somatic genomic testing in patients with cancer.

Precision medicine has revolutionized clinical care for patients with cancer through the development of targeted therapy, identification of inherited cancer predisposition syndromes and the use of pharmacogenetics to optimize pharmacotherapy for anticancer drugs and supportive care medications. While germline (patient) and somatic (tumor) genomic testing have evolved separately, recent interest in paired germline/somatic testing has led to an increase in integrated genomic testing workflows. However, paired germline/somatic testing has generally lacked the incorporation of germline pharmacogenomics. Integrating pharmacogenomics into paired germline/somatic genomic testing would be an efficient method for increasing access to pharmacogenomic testing. In this perspective, the authors argue for the benefits of implementing a comprehensive approach integrating somatic and germline testing that is inclusive of pharmacogenomics in clinical practice.

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

Introduction: Pharmacogenetics (PGx) has the potential to improve health outcomes but cost of testing is a barrier for equitable access. Reimbursement by insurance providers may lessen the financial burden for patients, but the extent to which PGx claims are covered in clinical practice has not been well-characterized in the literature. Methods: A retrospective analysis of outpatient claims submitted to payers for PGx tests from 1/1/2019 through 12/31/2021 was performed. A reimbursement rate was calculated and compared across specific test types (e.g., single genes, panel), payers, indication, and the year the claim was submitted. Results: A total of 1,039 outpatient claims for PGx testing were analyzed. The overall reimbursement rate was 46% and ranged from 36%-48% across payers. PGx panels were reimbursed at a significantly higher rate than single gene tests (74% vs. 43%, p < 0.001). Discussion: Reimbursement of claims for PGx testing is variable based on the test type, indication, year the claim was submitted, number of diagnosis codes submitted, and number of unique diagnosis codes submitted. Due to the highly variable nature of reimbursement, cost and affordability should be discussed with each patient.

Augmented reality-based training versus standard training in improvement of balance, mobility and fall risk: a systematic review and meta-analysis.

Augmented reality (AR) technology is being used recently in healthcare, especially for rehabilitation purposes, owing to its ability for repetition, rapid feedback, and motivation for patients. This systematic review and meta-analysis aims to compare the efficacy of AR-based interventions to conventional physical interventions in improving balance, mobility, and fall risk. Material and methods: PubMed, Google Scholar, Scopus, and the Cochrane Central Register of Controlled Trials were systematically searched from inception to January 2023. Randomized trials and observational cohort studies comparing the effects of AR-based exercises with conventional training in patients 18 years and older were included in the analysis. Studies using virtual reality, case reports and series, reviews, meta-analyses, letters, and editorials were excluded. Post-intervention data on the Berg Balance Scale (BBS) and Timed Up and Go (TUG) Test were extracted and studied. The fixed-effects inverse variance model was utilized to pool the extracted data. Results: Out of 438 articles, seven articles (199 participants) comparing AR-based exercise with the standard training were included in the systematic review. Six articles with sufficient data on the parameters were included in the meta-analysis. AR-based exercises resulted in a significantly higher BBS score than conventional exercise (Hedge's g=0.48, 95% CI=0.19-0.77, P<0.001). The BBS value was significantly higher in AR-based training of 8 weeks or more (Hedge's g=0.88, 95% CI=0.46-1.31) when compared with trainings conducted for less than 8 weeks (Hedge's g=0.11, 95% CI=-0.30 to 0.52), P=0.01). Likewise, the TUG Test score was found to be to be significantly lower in ARgroup than the controls (Hedge's g= -0.54, 95% CI=-0.85 to -0.23, P<0.01). Conclusion: In comparison to conventional methods, AR-based exercises had higher improvements in balance, mobility, and fall risk parameters. The use of AR technology in elderly patients can promote independence while preventing falls and associated morbidity and mortality. There is a need for a larger randomized controlled trial to provide a more accurate comparison on efficacy and safety of different modalities of training.

Implementation of CYP2C19 genotyping to guide proton pump inhibitor use at an academic health center.

PURPOSE: To describe the implementation of CYP2C19 testing into clinical practice at University of Florida (UF) Health Gainesville hospital to guide proton pump inhibitor (PPI) dosing and the lessons learned from this experience. SUMMARY: Different CYP2C19 genotypes are associated with variability in PPI plasma concentrations and intragastric pH, which may contribute to the risk of treatment failure due to subtherapeutic concentrations and adverse effects (eg, infection, bone fracture, renal dysfunction) with sustained supratherapeutic concentrations. Based on evidence available prior to the availability of pertinent Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, the UF Health Precision Medicine Program (PMP) developed clinical recommendations, provided through automated alerts at the time of a PPI order, to (1) increase the PPI dose for individuals with genotypes linked to increased CYP2C19 enzyme activity (ie, rapid and ultrarapid metabolizers) to improve the likelihood of drug effectiveness and (2) decrease the dose for individuals with decreased CYP2C19 activity (ie, intermediate and poor metabolizers) to reduce the risk of harm. The CYP2C19-PPI implementation was an iterative process that taught us key implementation lessons. Most notably, physician engagement is essential, problem lists in the medical record are unreliable, and special populations (eg, pediatric patients) need to be considered. CONCLUSION: Guiding PPI prescribing based on CYP2C19 genotype is a practical approach to potentially improve the benefit-risk ratio with PPI therapy. Physician engagement is key for successful implementation. A CPIC guideline on CYP2C19 genotype-guided PPI dosing is now available, and automated alerts may be instituted to facilitate implementation.

Rhino-Orbital Cerebral Mucormycosis in a Non-diabetic Patient Following COVID-19 Infection: A Case Report and Literature Review.

Rhino-orbital cerebral mucormycosis has been commonly seen during the coronavirus disease 2019 (COVID-19) pandemic. Several factors responsible for etiology and pathophysiology have been identified, among which corticosteroids and diabetes have contributed to the lion's share of the outbreak of mucormycosis. In this report, we discuss a case of a 41-year-old non-diabetic male with a recent convalescence from COVID-19 infection presented with gradual vision loss and loss of sensations in his right eye. He was found to have periorbital swelling, restriction of extraocular movements in all gazes, chemosis, ptosis of the right eye, and right maxillary sinus tenderness. His serum investigations, radiologic findings, and blood culture were indicative of rhino-orbital cerebral mucormycosis. He was started on systemic liposomal amphotericin B immediately and underwent aggressive surgical debridement. A high index of clinical suspicion, aggressive multifaceted management, and follow-up are needed to have successful outcomes, thereby lowering the morbidity of coronavirus-associated mucormycosis.

Variant Interpretation in Current Pharmacogenetic Testing.

In the current marketplace, there are now more than a dozen commercial companies providing pharmacogenetic tests. Each company varies in the panel of genes they test and the variants they are able to screen for. The reports generated by these companies provide phenotypic interpretations of pharmacogenes and clinically actionable gene-drug interactions based on internally curated data and proprietary algorithms. The freedom to choose the types of evidence to include versus exclude in interpreting genomics has created reporting discrepancies in the industry. The case report presented here reveals the discordant phenotype analysis provided by two pharmacogenetic testing companies. The uncertainty and unnecessary distress experienced by the patient highlights the need for consensus in phenotype reporting within the industry.