Incidence of statin-associated muscle symptoms in patients taking statins with RYR1 or CACNA1S variants.

Background: Statins are commonly used medications. Variants in SLCO1B1, CYP2C9, and ABCG2 are known predictors of muscle effects when taking statins. More exploratory genes include RYR1 and CACNA1S, which can also be associated with disease conditions. Methods: Patients with pathogenic/likely pathogenic variants in RYR1 or CACNA1S were identified through an elective genomic testing program. Through chart review, patients with a history of statin use were assessed for statin-associated muscle symptoms (SAMS) along with collection of demographics and other known risk factors for SAMS. Results: Of the 23 patients who had a pathogenic or likely pathogenic RYR1 or CACNA1S variant found, 12 had previous statin use; of these, SAMS were identified in four patients. Conclusion: These data contribute to previous literature suggesting patients with RYR1 variants may have an increased SAMS risk. Additional research will be helpful in further investigating this relationship and providing recommendations.

Implementation of CYP2C19 and CYP2D6 genotyping to guide antidepressant use in a large rural health system.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: We describe the implementation and ongoing maintenance of CYP2C19 and CYP2D6 focused pharmacogenetic (PGx) testing to guide antidepressant and antianxiety medication prescriptions in a large rural, nonprofit health system. SUMMARY: Depression and anxiety are common psychiatric conditions. Sanford Health implemented PGx testing for metabolism of cytochrome P450 (CYP) isozymes 2C19 and 2D6 in 2014 to inform prescribing for multiple medications, including antidepressant and antianxiety therapies. As guidelines, genotype to phenotype translation, panel offerings, and other resources are updated, we adapt our approach. We make educational and informational materials available to providers and patients. Pharmacogenomic clinical pharmacists review PGx results with discrete values and provide guidance documentation in the electronic medical record. A robust clinical decision support system is in place to provide interruptive alerts, noninterruptive alerts, and genomic indicators. A referral-based interdisciplinary clinic is also available to provide in-depth education to patients regarding PGx results and implications. Additionally, partnering with our health plan has expanded access to PGx testing for patients with anxiety or depression. CONCLUSION: The implementation and maintenance of Sanford Health's PGx program to guide antidepressant and antianxiety medication use continues to evolve and requires a multipronged approach relying on both human and informatics-based resources.

Clinical impact of preemptive pharmacogenomic testing on antiplatelet therapy in a real-world setting.

CYP2C19 genotyping to guide antiplatelet therapy after patients develop acute coronary syndromes (ACS) or require percutaneous coronary interventions (PCIs) reduces the likelihood of major adverse cardiovascular events (MACE). Evidence about the impact of preemptive testing, where genotyping occurs while patients are healthy, is lacking. In patients initiating antiplatelet therapy for ACS or PCI, we compared medical records data from 67 patients who received CYP2C19 genotyping preemptively (results >7 days before need), against medical records data from 67 propensity score-matched patients who received early genotyping (results within 7 days of need). We also examined data from 140 patients who received late genotyping (results >7 days after need). We compared the impact of genotyping approaches on medication selections, specialty visits, MACE and bleeding events over 1 year. Patients with CYP2C19 loss-of-function alleles were less likely to be initiated on clopidogrel if they received preemptive rather than early or late genotyping (18.2%, 66.7%, and 73.2% respectively, p = 0.001). No differences were observed by genotyping approach in the number of specialty visits or likelihood of MACE or bleeding events (all p > 0.21). Preemptive genotyping had a strong impact on initial antiplatelet selection and a comparable impact on patient outcomes and healthcare utilization, compared to genotyping ordered after a need for antiplatelet therapy had been identified.

Evolution of pharmacogenomic services and implementation of a multi-state pharmacogenomics clinic across a large rural healthcare system.

Introduction: Pharmacogenomics (PGx) aims to maximize drug benefits while minimizing risk of toxicity. Although PGx has proven beneficial in many settings, clinical uptake lags. Lack of clinician confidence and limited availability of PGx testing can deter patients from completing PGx testing. A few novel PGx clinic models have been described as a way to incorporate PGx testing into the standard of care. Background: A PGx clinic was implemented to fill an identified gap in provider availability, confidence, and utilization of PGx across our health system. Through a joint pharmacist and Advanced Practice Provider (APP) collaborative clinic, patients received counseling and PGx medication recommendations both before and after PGx testing. The clinic serves patients both in-person and virtually across four states in the upper Midwest. Results: The majority of patients seen in the PGx clinic during the early months were clinician referred (77%, n = 102) with the remainder being self-referred. Patients were, on average, taking two medications with Clinical Pharmacogenetics Implementation Consortium guidelines. Visits were split almost equally between in-person and virtual visits. Conclusion: Herein, we describe the successful implementation of an interdisciplinary PGx clinic to further enhance our PGx program. Throughout the implementation of the PGx clinic we have learned valuable lessons that may be of interest to other implementors. Clinicians were actively engaged in clinic referrals and early adoption of telemedicine was key to the clinic's early successes.

Congruence rates for pharmacogenomic noninterruptive alerts.

Meaningful clinical decision support (CDS) recommendations are vital for implementation of pharmacogenomics (PGx) into routine clinical care. PGx CDS alerts include interruptive and noninterruptive alerts. The objective of this study was to evaluate provider ordering behavior after noninterruptive alerts are displayed. A retrospective manual chart review was conducted from the time of noninterruptive alert implementation to the time of data analysis to determine congruence with CDS recommendations. The congruence rate for noninterruptive alerts was 89.8% across all drug-gene interactions. The drug-gene interaction with the most alerts for analysis included metoclopramide (n = 138). The high rate of medication order congruence after noninterruptive alerts were deployed suggests this modality may be appropriate for PGx CDS as a method for best practice adherence.

Attitudes about pharmacogenomic testing vary by healthcare specialty.

Aim: To understand how attitudes toward pharmacogenomic (PGx) testing among healthcare providers varies by specialty. Methods: Providers reported comfort ordering PGx testing and its perceived utility on web-based surveys before and after genetics education. Primary quantitative analyses compared primary care providers (PCPs) to specialty providers at both timepoints. Results: PCPs were more likely than specialty care providers to rate PGx testing as useful at both timepoints. Education increased comfort ordering PGx tests, with larger improvements among PCPs than specialty providers. Over 90% of cardiology and internal medicine providers rated PGx testing as useful at pre- and post-education. Conclusion: PCPs overwhelmingly perceive PGx to be useful, and provider education is particularly effective for improving PCPs' confidence. Education for all specialties will be essential to ensure appropriate integration into routine practice.

Impact of transitioning to an active, noninterruptive CYP2C19/proton pump inhibitor alert on prescribing patterns.

PURPOSE: To compare rates of prescriber acceptance of interruptive and noninterruptive clinical decision support (CDS) alerts regarding potential diminished therapeutic effectiveness and safety risks associated with proton pump inhibitor (PPI) use in carriers of gene variants affecting cytochrome P450 (CYP) isozyme 2C19 metabolism. METHODS: A retrospective study was conducted at a large rural health system to examine different approaches to improving CDS alert acceptance while minimizing alert fatigue. Manual reviews were conducted to identify alerts regarding CYP2C19 metabolizer status displayed at the time of PPI ordering over 30-day periods before and after the transition from interruptive to noninterruptive CDS alert functionality. A chi-square test was conducted to analyze prescriber acceptance of CDS recommendations by alert modality and type of treatment modification. RESULTS: Overall, interruptive alerts had an acceptance rate of 18.6% (64/344), compared to 8.4% acceptance (30/357 alerts) for noninterruptive alerts (P ≤ 0.0001). Analysis of acceptance criteria -revealed the noninterruptive alert cohort had higher acceptance, as determined by documented medication dose adjustments, than the interruptive alert cohort (53.3% [16/30] and 4.7% [3/64], respectively). The difference in acceptance rates by CDS modality and treatment modification was statistically significant (P ≤ 0.00001). The predominant indication for PPI use was gastroesophageal reflux disease (GERD) in both cohorts. CONCLUSION: Interruptive alerts that actively influenced workflow had higher acceptance rates than noninterruptive alerts that served an informational purpose without a direct disruption of workflow. The study results suggest the utilization of noninterruptive alerts may be a beneficial tool for prompting clinicians to alter dosing regimens rather than transition to an alternative agent.

SLCO1B1 gene-based clinical decision support reduces statin-associated muscle symptoms risk with simvastatin.

Background: SLCO1B1 variants are known to be a strong predictor of statin-associated muscle symptoms (SAMS) risk with simvastatin. Methods: The authors conducted a retrospective chart review on 20,341 patients who had SLCO1B1 genotyping to quantify the uptake of clinical decision support (CDS) for genetic variants known to impact SAMS risk. Results: A total of 182 patients had 417 CDS alerts generated, and 150 of these patients (82.4%) received pharmacotherapy that did not increase risks for SAMS. Providers were more likely to cancel simvastatin orders in response to CDS alerts if genotyping had been done prior to the first simvastatin prescription than after (94.1% vs 28.5%, respectively; p < 0.001). Conclusion: CDS significantly reduces simvastatin prescribing at doses associated with SAMS.

Patient satisfaction with return of pharmacogenomic results utilizing a patient portal message.

Background: Returning pharmacogenomics (PGx) results to patients is complex and challenging. Patients prefer provider education; however, a gap in provider comfort in PGx results has been documented. Objectives: This study's purpose was to evaluate satisfaction with the return of PGx test results using a patient portal message. Methods: A survey was sent to two cohorts with PGx results, one that received a PGx result message and one that did not. Results: Following implementation of the PGx result message, there was a decrease in patients reporting negative responses surrounding satisfaction in the return of their PGx results, with 39% responding negatively pre-implementation and 21% post-implementation. Conclusion: Satisfaction with the return of results improved following the implementation of a patient portal message.

Metoprolol and CYP2D6: A Retrospective Cohort Study Evaluating Genotype-Based Outcomes.

Metoprolol is a medication commonly utilized in select patients to achieve a reduction in heart rate, systolic blood pressure, or other indications. A majority of metoprolol metabolism occurs via CYP2D6. Decreased expression of the CYP2D6 enzyme increases the concentration of metoprolol. Current pharmacogenomics guidelines by the Dutch Pharmacogenomics Working Group recommend slower titrations and dose decreases to minimize adverse effects from poor metabolizers or normal metabolizers taking concomitant medications that are strong inhibitors of CYP2D6 (phenoconverters). This study aimed to evaluate adverse effects such as bradycardia, hypotension, and syncope in patients who are expected to have absent CYP2D6 enzyme activity due to drug-drug or drug-gene interactions. The secondary aims of this study were to evaluate heart rate measurements for the included participants. Retrospective data were collected for individuals with CYP2D6 genotyping results obtained for clinical purposes. Three categories (CYP2D6 normal metabolizers, poor metabolizers, and phenoconverters) were assigned. A total of 325 participants were included. There was no statistically significant difference found in the primary composite outcome between the three metabolizer groups (p = 0.054). However, a statistically significant difference was identified in the incidences of bradycardia between the poor metabolizers and the normal metabolizers or phenoconverters (p < 0.0001). The average heart rates were 2.8 beats per minute (bpm) and 2.6 bpm lower for the poor metabolizer and phenoconverter groups, respectively, compared to the normal metabolizers (p < 0.0001 for both comparisons). This study further supports the role of genetic testing in precision medicine to help individualize patient care as CYP2D6 poor metabolizers taking metoprolol were found to have an increase in bradycardia. Additional research is needed to clarify the dose relationship in this drug-gene interaction.

Leveraging clinical decision support to reduce the risk of discordant pharmacogenomics results.

Pharmacogenomics (PGx) testing is commonly utilized to predict a patient's response to medications based on the presence of genetic variants. However, certain conditions have been associated with potentially inaccurate PGx results. The majority of medications are predominantly metabolized in the liver; therefore, in the case of liver transplantation, PGx results may be misinterpreted in the context of drug-metabolizing enzymes. Other instances of ambiguous PGx results have been reported in the literature in conditions such as allogeneic stem cell or bone marrow transplant, chronic lymphocytic leukemia, acute or chronic myeloid leukemia and blood transfusion. In order to prevent potential inaccuracies in PGx testing, Sanford Imagenetics developed an active, interruptive alert to inform providers of the potential for inaccurate PGx results.

Progression of precision statin prescribing for reduction of statin-associated muscle symptoms.

Background: Statins are among the most commonly prescribed medications, and improve patient outcomes by lowering cholesterol levels, but also have side effects. Variations in statin response can be attributed to a handful of factors that include pharmacogenetics. Methods: While not a true review article, this work was written using various search engines and terms and previous and newly published Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for statins to provide a historical perspective in addition to the current status of statin-related pharmacogenetics and future perspectives. Results: This article provides historical background on statins and associated adverse effects, reviews pharmacogenetic implications, applies clinical decision support, incorporates the latest CPIC guidelines and addresses future implications. Conclusion: Statins are a beneficial medication, but not without risk. Pharmacogenomics can help mitigate some risk factors. Clinical decision support, implementation, research and guidelines will continue to influence statin prescribing.

The effect of medication reconciliation on generating an accurate medication list in a pharmacogenomics practice.

Background: Medication reconciliation is recognized as a critically important medication safety element and a key initiative by multiple organizations. Within our precision medicine program, accurate medication lists are essential to our ability to make specific medication recommendations based on pharmacogenetic results. Our study aimed to identify discrepancies within the patient's medication list to improve medication management via genetic factors through a pharmacy team-based approach. Methods: A dedicated team of pharmacists and trained student pharmacists conducted telephone interviews to complete medication reconciliation for individuals enrolled in our precision medicine preemptive screening program. Medication list discrepancies were tracked as well as if pharmacogenetic consults were altered by findings during the telephone interviews. Results: Medication reconciliation was completed on 465 participants who had recently received or were awaiting pharmacogenetic testing. We found similar results to previously described rates of medication list discrepancies with an average of 4.9 medication discrepancies per patient as well as greater than 90% of individuals having at least one medication discrepancy. Pharmacogenetic recommendations for 20 individuals (4.3%) required adjustment following medication reconciliation. Conclusions: This pilot program supports the value of a dedicated team for medication reconciliation and the importance of accurate medication lists to optimize precision medicine programs.

Malignant hyperthermia susceptibility: utilization of genetic results in an electronic medical record to increase safety.

Aim: This manuscript describes implementation of clinical decision support for providers concerned with perioperative complications of malignant hyperthermia susceptibility. Materials & methods: Clinical decision support for malignant hyperthermia susceptibility was implemented in 2018 based around our pre-emptive genotyping platform. We completed a brief descriptive review of patients who underwent pre-emptive testing, focused particularly on RYR1 and CACNA1S genes. Results: To date, we have completed pre-emptive genetic testing on more than 10,000 patients; 13 patients having been identified as a carrier of a pathogenic or likely pathogenic variant of RYR1 or CACNA1S. Conclusion: An alert system for malignant hyperthermia susceptibility - as an extension of our pre-emptive genomics platform - was implemented successfully. Implementation strategies and lessons learned are discussed herein.

Implementation of wide-scale pharmacogenetic testing in primary care.

The convergence of translational genomics and biomedical informatics has changed healthcare delivery. Institutional consortia have begun implementing lab testing and decision support for drug-gene interactions. Aggregate datasets are now revealing the impact of clinical decision support for drug-gene interactions. Given the pleiotropic nature of pharmacogenes, interdisciplinary teams and robust clinical decision support tools must exist within an informatics framework built to be flexible and capable of cross-talk between clinical specialties. Navigation of the challenges presented with the implementation of five steps to build a genetics program infrastructure requires the expertise of multiple healthcare professionals. Ultimately, this manuscript describes our efforts to place pharmacogenomics in the hands of the primary care provider integrating this information into a patient's healthcare over their lifetime.