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Zoltick ES, Bell M, Hickingbotham MR, Wu AC, Galbraith LN, LeBlanc JL, Lu CY, Leonhard JR, Platt DM, Smith HS, Green RC, Hajek C, Christensen KD. Attitudes, knowledge, and risk perceptions of patients who received elective genomic testing as a clinical service. Genet Med 2024; 26:101200. [PMID: 38943480 PMCID: PMC11456384 DOI: 10.1016/j.gim.2024.101200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 06/20/2024] [Accepted: 06/21/2024] [Indexed: 07/01/2024] Open
Abstract
PURPOSE Elective genomic testing (EGT) is increasingly available clinically. Limited real-world evidence exists about attitudes and knowledge of EGT recipients. METHODS After web-based education, patients who enrolled in an EGT program at a rural nonprofit health care system completed a survey that assessed attitudes, knowledge, and risk perceptions. RESULTS From August 2020 to April 2022, 5920 patients completed the survey and received testing. Patients most frequently cited interest in learning their personal disease risks as their primary motivation. Patients most often expected results to guide medication management (74.0%), prevent future disease (70.4%), and provide information about risks to offspring (65.4%). Patients were "very concerned" most frequently about the privacy of genetic information (19.8%) and how well testing predicted disease risks (18.0%). On average, patients answered 6.7 of 11 knowledge items correctly (61.3%). They more often rated their risks for colon and breast cancers as lower rather than higher than the average person but more often rated their risk for a heart attack as higher rather than lower than the average person (all P < .001). CONCLUSION Patients pursued EGT because of the utility expectations but often misunderstood the test's capabilities.
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Affiliation(s)
- Emilie S Zoltick
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA
| | - Megan Bell
- Sanford Imagenetics, Sioux Falls, SD; Department of Genetic Counseling, Augustana University, Sioux Falls, SD.
| | | | - Ann Chen Wu
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA; Department of Population Medicine, Harvard Medical School, Boston, MA
| | - Lauren N Galbraith
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA; Pfizer, Inc, New York, NY
| | - Jessica L LeBlanc
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA
| | - Christine Y Lu
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA; Department of Population Medicine, Harvard Medical School, Boston, MA; Kolling Institute, Faculty of Medicine and Health, The University of Sydney and the Northern Sydney Local Health District, Sydney, NSW, Australia; School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | | | - Dylan M Platt
- Sanford Imagenetics, Sioux Falls, SD; Department of Genetic Counseling, Augustana University, Sioux Falls, SD
| | - Hadley Stevens Smith
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA; Department of Population Medicine, Harvard Medical School, Boston, MA
| | - Robert C Green
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Ariadne Labs, Boston, MA; The Broad Institute of Harvard and MIT, Cambridge, MA
| | - Catherine Hajek
- Sanford Imagenetics, Sioux Falls, SD; Helix Inc, San Mateo, CA
| | - Kurt D Christensen
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA; Department of Population Medicine, Harvard Medical School, Boston, MA; The Broad Institute of Harvard and MIT, Cambridge, MA
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Massmann A, Heukelom JV, Weaver M, Schultz A, Figueroa DM, Stys A, Stys TP, Christensen KD. Evaluation of pharmacogenetic automated clinical decision support for clopidogrel. Pharmacogenomics 2024; 25:391-399. [PMID: 39258919 PMCID: PMC11418215 DOI: 10.1080/14622416.2024.2394014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Accepted: 08/15/2024] [Indexed: 09/12/2024] Open
Abstract
Aim: Clopidogrel requires CYP2C19 activation to have antiplatelet effects. Pharmacogenetic testing to identify patients with impaired CYP2C19 function can be coupled with clinical decision support (CDS) alerts to guide antiplatelet prescribing. We evaluated the impact of alerts on clopidogrel prescribing.Materials & methods: We retrospectively analyzed data for 866 patients in which CYP2C19-clopidogrel CDS was deployed at a single healthcare system during 2015-2023.Results: Analyses included 2,288 alerts. CDS acceptance rates increased from 24% in 2015 to 63% in 2023 (p < 0.05). Adjusted analyses also showed higher acceptance rates when clopidogrel had been ordered for a percutaneous intervention (OR: 28.7, p < 0.001) and when cardiologists responded to alerts (OR: 2.11, p = 0.001).Conclusion: CDS for CYP2C19-clopidogrel was effective in reducing potential drug-gene interactions. Its influence varied by clinician specialty and medication indications.
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Affiliation(s)
- Amanda Massmann
- Sanford Imagenetics, Sioux Falls, SD57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD57069, USA
| | - Joel Van Heukelom
- Sanford Imagenetics, Sioux Falls, SD57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD57069, USA
| | - Max Weaver
- Sanford Imagenetics, Sioux Falls, SD57105, USA
| | - April Schultz
- Sanford Imagenetics, Sioux Falls, SD57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD57069, USA
| | - Debbie M Figueroa
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD57069, USA
- Sanford Medical Genetics Laboratory, Sioux Falls, SD57105, USA
| | - Adam Stys
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD57069, USA
- Sanford Cardiovascular Institute, Sioux Falls, SD57105, USA
| | - Tomasz P Stys
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD57069, USA
- Sanford Cardiovascular Institute, Sioux Falls, SD57105, USA
| | - Kurt D Christensen
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute & Harvard Medical School, Boston, MA02215, USA
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Massmann A, Christensen KD, Van Heukelom J, Schultz A, Shaukat MHS, Hajek C, Weaver M, Green RC, Wu AC, Hickingbotham MR, Zoltick ES, Stys A, Stys TP. Clinical impact of preemptive pharmacogenomic testing on antiplatelet therapy in a real-world setting. Eur J Hum Genet 2024; 32:895-902. [PMID: 38424298 PMCID: PMC11291480 DOI: 10.1038/s41431-024-01567-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 02/06/2024] [Accepted: 02/08/2024] [Indexed: 03/02/2024] Open
Abstract
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.
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Affiliation(s)
- Amanda Massmann
- Sanford Imagenetics, Sioux Falls, SD, 57105, USA.
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, 57069, USA.
| | - Kurt D Christensen
- Broad Institute of Harvard and MIT, Cambridge, MA, 02141, USA
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA, 02215, USA
| | - Joel Van Heukelom
- Sanford Imagenetics, Sioux Falls, SD, 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, 57069, USA
| | - April Schultz
- Sanford Imagenetics, Sioux Falls, SD, 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, 57069, USA
| | - Muhammad Hamza Saad Shaukat
- Minneapolis Heart Institute/Abbott Northwestern Hospital Institute, Minneapolis, MN, 55407, USA
- Sanford Cardiovascular Institute, Sioux Falls, SD, 57105, USA
| | - Catherine Hajek
- Sanford Imagenetics, Sioux Falls, SD, 57105, USA
- Helix OpCo, LLC, San Mateo, CA, 94401, USA
| | - Max Weaver
- Sanford Imagenetics, Sioux Falls, SD, 57105, USA
| | - Robert C Green
- Broad Institute of Harvard and MIT, Cambridge, MA, 02141, USA
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
- Ariadne Labs, Boston, MA, 02215, USA
| | - Ann Chen Wu
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA, 02215, USA
| | - Madison R Hickingbotham
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Emilie S Zoltick
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Adam Stys
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, 57069, USA
- Sanford Cardiovascular Institute, Sioux Falls, SD, 57105, USA
| | - Tomasz P Stys
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, 57069, USA
- Sanford Cardiovascular Institute, Sioux Falls, SD, 57105, USA
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Deininger KM, Anderson HD, Patrinos GP, Mitropoulou C, Aquilante CL. Cost-effectiveness analysis of CYP3A5 genotype-guided tacrolimus dosing in solid organ transplantation using real-world data. THE PHARMACOGENOMICS JOURNAL 2024; 24:14. [PMID: 38750044 DOI: 10.1038/s41397-024-00334-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 04/05/2024] [Accepted: 04/23/2024] [Indexed: 06/15/2024]
Abstract
The objective of this study was to estimate the cost-effectiveness of CYP3A5 genotype-guided tacrolimus dosing in kidney, liver, heart, and lung transplant recipients relative to standard of care (SOC) tacrolimus dosing, from a US healthcare payer perspective. We developed decision-tree models to compare economic and clinical outcomes between CYP3A5 genotype-guided and SOC tacrolimus therapy in the first six months post-transplant. We derived inputs for CYP3A5 phenotype frequencies and physician use of genotype test results to inform clinical care from literature; tacrolimus exposure [high vs low tacrolimus time in therapeutic range using the Rosendaal algorithm (TAC TTR-Rosendaal)] and outcomes (incidences of acute tacrolimus nephrotoxicity, acute cellular rejection, and death) from real-world data; and costs from the Medicare Fee Schedule and literature. We calculated cost per avoided event and performed sensitivity analyses to evaluate the robustness of the results to changes in inputs. Incremental costs per avoided event for CYP3A5 genotype-guided vs SOC tacrolimus dosing were $176,667 for kidney recipients, $364,000 for liver recipients, $12,982 for heart recipients, and $93,333 for lung recipients. The likelihood of CYP3A5 genotype-guided tacrolimus dosing leading to cost-savings was 19.8% in kidney, 32.3% in liver, 51.8% in heart, and 54.1% in lung transplant recipients. Physician use of genotype results to guide clinical care and the proportion of patients with a high TAC TTR-Rosendaal were key parameters driving the cost-effectiveness of CYP3A5 genotype-guided tacrolimus therapy. Relative to SOC, CYP3A5 genotype-guided tacrolimus dosing resulted in a slightly greater benefit at a higher cost. Further economic evaluations examining intermediary outcomes (e.g., dose modifications) are needed, particularly in populations with higher frequencies of CYP3A5 expressers.
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Affiliation(s)
- Kimberly M Deininger
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA
| | - Heather D Anderson
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA
| | - George P Patrinos
- Department of Pharmacy, University of Patras School of Health Sciences, Patras, Greece
- Department of Genetics and Genomics, United Arab Emirates University, College of Medicine and Health Sciences, Al-Ain, Abu Dhabi, UAE
- Zayed Center for Health Sciences, United Arab Emirates University, Al-Ain, Abu Dhabi, UAE
| | - Christina Mitropoulou
- Department of Genetics and Genomics, United Arab Emirates University, College of Medicine and Health Sciences, Al-Ain, Abu Dhabi, UAE
- The Golden Helix Foundation, London, UK
| | - Christina L Aquilante
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA.
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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5
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Petry NJ, Massmann A, Bell M, Schultz A, Heukelom JV. Incidence of statin-associated muscle symptoms in patients taking statins with RYR1 or CACNA1S variants. Per Med 2024; 21:145-150. [PMID: 38722226 DOI: 10.1080/17410541.2024.2342223] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 04/09/2024] [Indexed: 07/26/2024]
Abstract
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.
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Affiliation(s)
- Natasha J Petry
- Department of Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Pharmacy Practice, North Dakota State University, Fargo, ND 58108, USA
| | - Amanda Massmann
- Department of Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Megan Bell
- Department of Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Genetic Counseling, Augustana University, Sioux Falls, SD 57197, USA
| | - April Schultz
- Department of Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Joel Van Heukelom
- Department of Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
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Johnson D, Del Fiol G, Kawamoto K, Romagnoli KM, Sanders N, Isaacson G, Jenkins E, Williams MS. Genetically guided precision medicine clinical decision support tools: a systematic review. J Am Med Inform Assoc 2024; 31:1183-1194. [PMID: 38558013 PMCID: PMC11031215 DOI: 10.1093/jamia/ocae033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/06/2024] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
OBJECTIVES Patient care using genetics presents complex challenges. Clinical decision support (CDS) tools are a potential solution because they provide patient-specific risk assessments and/or recommendations at the point of care. This systematic review evaluated the literature on CDS systems which have been implemented to support genetically guided precision medicine (GPM). MATERIALS AND METHODS A comprehensive search was conducted in MEDLINE and Embase, encompassing January 1, 2011-March 14, 2023. The review included primary English peer-reviewed research articles studying humans, focused on the use of computers to guide clinical decision-making and delivering genetically guided, patient-specific assessments, and/or recommendations to healthcare providers and/or patients. RESULTS The search yielded 3832 unique articles. After screening, 41 articles were identified that met the inclusion criteria. Alerts and reminders were the most common form of CDS used. About 27 systems were integrated with the electronic health record; 2 of those used standards-based approaches for genomic data transfer. Three studies used a framework to analyze the implementation strategy. DISCUSSION Findings include limited use of standards-based approaches for genomic data transfer, system evaluations that do not employ formal frameworks, and inconsistencies in the methodologies used to assess genetic CDS systems and their impact on patient outcomes. CONCLUSION We recommend that future research on CDS system implementation for genetically GPM should focus on implementing more CDS systems, utilization of standards-based approaches, user-centered design, exploration of alternative forms of CDS interventions, and use of formal frameworks to systematically evaluate genetic CDS systems and their effects on patient care.
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Affiliation(s)
- Darren Johnson
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Katrina M Romagnoli
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Nathan Sanders
- School of Medicine, Geisinger Health Systems, Danville, PA 17822, United States
| | - Grace Isaacson
- Family Medicine, Penn Highlands Healthcare, DuBois, PA 16830, United States
| | - Elden Jenkins
- School of Medicine, Noorda College of Osteopathic Medicine, Provo, UT 84606, United States
| | - Marc S Williams
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
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Van Heukelom J, Morgan J, Massmann A, Jacobsen K, Petry NJ, Baye JF, Frear S, Schultz A. Evolution of pharmacogenomic services and implementation of a multi-state pharmacogenomics clinic across a large rural healthcare system. Front Pharmacol 2023; 14:1274165. [PMID: 38035031 PMCID: PMC10682150 DOI: 10.3389/fphar.2023.1274165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023] Open
Abstract
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.
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Affiliation(s)
- Joel Van Heukelom
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD, United States
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, United States
| | - Jennifer Morgan
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD, United States
- Department of Medical Genetics, Sanford Health, Sioux Falls, SD, United States
| | - Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD, United States
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, United States
| | - Kristen Jacobsen
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD, United States
| | - Natasha J. Petry
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD, United States
- Department of Pharmacy Practice, North Dakota State University, Fargo, ND, United States
| | - Jordan F. Baye
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD, United States
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, United States
- Department of Pharmacy Practice, South Dakota State University College of Pharmacy and Allied Health Professions, Brookings, SD, United States
| | - Samantha Frear
- Translational Software, Inc., Mercer Island, WA, United States
| | - April Schultz
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD, United States
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, United States
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Principi N, Petropulacos K, Esposito S. Impact of Pharmacogenomics in Clinical Practice. Pharmaceuticals (Basel) 2023; 16:1596. [PMID: 38004461 PMCID: PMC10675377 DOI: 10.3390/ph16111596] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/26/2023] Open
Abstract
Polymorphisms of genes encoding drug metabolizing enzymes and transporters can significantly modify pharmacokinetics, and this can be associated with significant differences in drug efficacy, safety, and tolerability. Moreover, genetic variants of some components of the immune system can explain clinically relevant drug-related adverse events. However, the implementation of drug dose individualization based on pharmacogenomics remains scarce. In this narrative review, the impact of genetic variations on the disposition, safety, and tolerability of the most commonly prescribed drugs is reported. Moreover, reasons for poor implementation of pharmacogenomics in everyday clinical settings are discussed. The literature analysis showed that knowledge of how genetic variations can modify the effectiveness, safety, and tolerability of a drug can lead to the adjustment of usually recommended drug dosages, improve effectiveness, and reduce drug-related adverse events. Despite some efforts to introduce pharmacogenomics in clinical practice, presently very few centers routinely use genetic tests as a guide for drug prescription. The education of health care professionals seems critical to keep pace with the rapidly evolving field of pharmacogenomics. Moreover, multimodal algorithms that incorporate both clinical and genetic factors in drug prescribing could significantly help in this regard. Obviously, further studies which definitively establish which genetic variations play a role in conditioning drug effectiveness and safety are needed. Many problems must be solved, but the advantages for human health fully justify all the efforts.
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Affiliation(s)
| | | | - Susanna Esposito
- Pediatric Clinic, Department of Medicine and Surgery, University Hospital of Parma, 43126 Parma, Italy
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Preys CL, Blout Zawatsky CL, Massmann A, Heukelom JV, Green RC, Hajek C, Hickingbotham MR, Zoltick ES, Schultz A, Christensen KD. Attitudes about pharmacogenomic testing vary by healthcare specialty. Pharmacogenomics 2023; 24:539-549. [PMID: 37458095 PMCID: PMC10621761 DOI: 10.2217/pgs-2023-0039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023] Open
Abstract
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.
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Affiliation(s)
- Charlene L Preys
- MGH Institute of Health Professions, Charlestown, MA 02129, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Carrie L Blout Zawatsky
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
- Ariadne Labs, Boston, MA 02215, USA
| | - Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermilion, SD 57069, USA
| | - Joel Van Heukelom
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermilion, SD 57069, USA
| | - Robert C Green
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
- Ariadne Labs, Boston, MA 02215, USA
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Catherine Hajek
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Helix OpCo, LLC, San Diego, CA 92121, USA
| | - Madison R Hickingbotham
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Emilie S Zoltick
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - April Schultz
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermilion, SD 57069, USA
| | - Kurt D Christensen
- Ariadne Labs, Boston, MA 02215, USA
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02115, USA
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10
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Fahim SM, Alexander CSW, Qian J, Ngorsuraches S, Hohmann NS, Lloyd KB, Reagan A, Hart L, McCormick N, Westrick SC. Current published evidence on barriers and proposed strategies for genetic testing implementation in health care settings: A scoping review. J Am Pharm Assoc (2003) 2023; 63:998-1016. [PMID: 37119989 DOI: 10.1016/j.japh.2023.04.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 04/20/2023] [Accepted: 04/22/2023] [Indexed: 05/01/2023]
Abstract
BACKGROUND The slow uptake of genetic testing in routine clinical practice warrants the attention of researchers and practitioners to find effective strategies to facilitate implementation. OBJECTIVES This study aimed to identify the barriers to and strategies for pharmacogenetic testing implementation in a health care setting from published literature. METHODS A scoping review was conducted in August 2021 with an expanded literature search using Ovid MEDLINE, Web of Science, International Pharmaceutical Abstract, and Google Scholar to identify studies reporting implementation of pharmacogenetic testing in a health care setting, from a health care system's perspective. Articles were screened using DistillerSR and findings were organized using the 5 major domains of Consolidated Framework for Implementation Research (CFIR). RESULTS A total of 3536 unique articles were retrieved from the above sources, with only 253 articles retained after title and abstract screening. Upon screening the full texts, 57 articles (representing 46 unique practice sites) were found matching the inclusion criteria. We found that most reported barriers and their associated strategies to the implementation of pharmacogenetic testing surrounded 2 CFIR domains: intervention characteristics and inner settings. Factors relating to cost and reimbursement were described as major barriers in the intervention characteristics. In the same domain, another major barrier was the lack of utility studies to provide evidence for genetic testing uptake. Technical hurdles, such as integrating genetic information to medical records, were identified as an inner settings barrier. Collaborations and lessons from early implementers could be useful strategies to overcome majority of the barriers across different health care settings. Strategies proposed by the included implementation studies to overcome these barriers are summarized and can be used as guidance in future. CONCLUSION Barriers and strategies identified in this scoping review can provide implementation guidance for practice sites that are interested in implementing genetic testing.
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11
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Mills SC, Massmann A. Congruence rates for pharmacogenomic noninterruptive alerts. Pharmacogenomics 2023; 24:493-500. [PMID: 37435734 DOI: 10.2217/pgs-2023-0016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2023] Open
Abstract
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.
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Affiliation(s)
- Sarah C Mills
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
| | - Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
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12
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Massmann A, Van Heukelom J, Green RC, Hajek C, Hickingbotham MR, Larson EA, Lu CY, Wu AC, Zoltick ES, Christensen KD, Schultz A. SLCO1B1 gene-based clinical decision support reduces statin-associated muscle symptoms risk with simvastatin. Pharmacogenomics 2023; 24:399-409. [PMID: 37232094 PMCID: PMC10242433 DOI: 10.2217/pgs-2023-0056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 05/09/2023] [Indexed: 05/27/2023] Open
Abstract
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.
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Affiliation(s)
- Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Joel Van Heukelom
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Robert C Green
- Department of Medicine, Brigham & Women's Hospital & Harvard Medical School, Boston, MA 02115, USA
- Ariadne Labs, Boston, MA 02215, USA
- Broad Institute of Harvard & MIT, Cambridge, MA 02142, USA
| | - Catherine Hajek
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Helix OpCo, LLC, San Mateo, CA 94401, USA
| | - Madison R Hickingbotham
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Eric A Larson
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Christine Y Lu
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Ann Chen Wu
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Emilie S Zoltick
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Kurt D Christensen
- Broad Institute of Harvard & MIT, Cambridge, MA 02142, USA
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - April Schultz
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
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13
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Heukelom JV, Jacobsen K, Petry NJ, Schultz A, Baye J, Sturdevant D, Massmann A. Patient satisfaction with return of pharmacogenomic results utilizing a patient portal message. Pharmacogenomics 2023; 24:315-323. [PMID: 37125619 PMCID: PMC10318570 DOI: 10.2217/pgs-2023-0032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 03/29/2023] [Indexed: 05/02/2023] Open
Abstract
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.
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Affiliation(s)
- Joel Van Heukelom
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Sanford School of Medicine, University of South Dakota, Vermillion, SD 57069, USA
| | | | - Natasha J Petry
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Pharmacy Practice, North Dakota State University, Fargo, ND 58102, USA
| | - April Schultz
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Sanford School of Medicine, University of South Dakota, Vermillion, SD 57069, USA
| | - Jordan Baye
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Sanford School of Medicine, University of South Dakota, Vermillion, SD 57069, USA
- College of Pharmacy & Allied Health Professions, South Dakota State University, Brookings, SD 57007, USA
| | | | - Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Sanford School of Medicine, University of South Dakota, Vermillion, SD 57069, USA
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14
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Metoprolol and CYP2D6: A Retrospective Cohort Study Evaluating Genotype-Based Outcomes. J Pers Med 2023; 13:jpm13030416. [PMID: 36983598 PMCID: PMC10058912 DOI: 10.3390/jpm13030416] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 02/15/2023] [Accepted: 02/23/2023] [Indexed: 03/02/2023] Open
Abstract
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.
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15
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Massmann A, Heukelom JV, Larson C, Starks RD. Leveraging clinical decision support to reduce the risk of discordant pharmacogenomics results. Pharmacogenomics 2022; 23:987-993. [PMID: 36454237 DOI: 10.2217/pgs-2022-0148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
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.
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Affiliation(s)
- Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA.,Sanford School of Medicine, University of South Dakota, Vermillion, SD 57105, USA
| | - Joel Van Heukelom
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA.,Sanford School of Medicine, University of South Dakota, Vermillion, SD 57105, USA
| | - Chad Larson
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA.,Sanford Health Technology Solutions, Sioux Falls, SD 57104, USA
| | - Rachel D Starks
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA.,Sanford School of Medicine, University of South Dakota, Vermillion, SD 57105, USA
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16
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Blout Zawatsky CL, Leonhard JR, Bell M, Moore MM, Petry NJ, Platt DM, Green RC, Hajek C, Christensen KD. Workforce Considerations When Building a Precision Medicine Program. J Pers Med 2022; 12:1929. [PMID: 36422106 PMCID: PMC9692406 DOI: 10.3390/jpm12111929] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/11/2022] [Accepted: 11/12/2022] [Indexed: 11/22/2022] Open
Abstract
This paper describes one healthcare system's approach to strategically deploying genetic specialists and pharmacists to support the implementation of a precision medicine program. In 2013, Sanford Health initiated the development of a healthcare system-wide precision medicine program. Here, we report the necessary staffing including the genetic counselors, genetic counseling assistants, pharmacists, and geneticists. We examined the administrative and electronic medical records data to summarize genetic referrals over time as well as the uptake and results of an enterprise-wide genetic screening test. Between 2013 and 2020, the number of genetic specialists employed at Sanford Health increased by 190%, from 10.1 full-time equivalents (FTEs) to 29.3 FTEs. Over the same period, referrals from multiple provider types to genetic services increased by 423%, from 1438 referrals to 7517 referrals. Between 2018 and 2020, 11,771 patients received a genetic screening, with 4% identified with potential monogenic medically actionable predisposition (MAP) findings and 95% identified with at least one informative pharmacogenetic result. Of the MAP-positive patients, 85% had completed a session with a genetics provider. A strategic workforce staffing and deployment allowed Sanford Health to manage a new genetic screening program, which prompted a large increase in genetic referrals. This approach can be used as a template for other healthcare systems interested in the development of a precision medicine program.
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Affiliation(s)
- Carrie L. Blout Zawatsky
- Genomes2People, Department of Medicine (Genetics), Brigham and Women’s Hospital, Boston, MA 02115, USA
- Broad Institute, Cambridge, MA 02142, USA
- Precision Population Health, Ariadne Labs, Boston, MA 02115, USA
- The MGH Institute of Health Professions, Boston, MA 02115, USA
| | | | - Megan Bell
- Department of Genetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Genetic Counseling, Augustana University, Sioux Falls, SD 57117, USA
| | | | - Natasha J. Petry
- Department of Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Pharmacy Practice, North Dakota State University, Fargo, ND 58105, USA
| | - Dylan M. Platt
- Department of Genetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Genetic Counseling, Augustana University, Sioux Falls, SD 57117, USA
| | - Robert C. Green
- Genomes2People, Department of Medicine (Genetics), Brigham and Women’s Hospital, Boston, MA 02115, USA
- Broad Institute, Cambridge, MA 02142, USA
- Precision Population Health, Ariadne Labs, Boston, MA 02115, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Catherine Hajek
- Department of Genetics, Sanford Health, Sioux Falls, SD 57117, USA
- Sanford School of Medicine, University of South Dakota, Sioux Falls, SD 57117, USA
- Helix, San Mateo, CA 94401, USA
| | - Kurt D. Christensen
- Broad Institute, Cambridge, MA 02142, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
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17
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Dusic EJ, Theoryn T, Wang C, Swisher EM, Bowen DJ. Barriers, interventions, and recommendations: Improving the genetic testing landscape. Front Digit Health 2022; 4:961128. [PMID: 36386046 PMCID: PMC9665160 DOI: 10.3389/fdgth.2022.961128] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 09/27/2022] [Indexed: 11/06/2022] Open
Abstract
Individual, provider, clinic, and societal level barriers have been shown to undermine the potential impact of genetic testing. The current approach in the primary care setting places an exorbitant burden on both providers and patients. Current literature provides insight into how to address barriers across multiple levels (patient, provider, clinic, system) and at multiple stages in the testing process (identification, referral, counseling, and testing) but interventions have had limited success. After outlining the current approach to genetic testing in the primary care setting, including the barriers that prevent genetic testing uptake and the methods proposed to address these issues, we recommend integrating genetic testing into routine medical care through population-based testing. Success in efforts to increase the uptake of genetic testing will not occur without significant changes to the way genetic services are delivered. These changes will not be instantaneous but are critical in moving this field forward to realize the potential for cancer risk genetic assessment to reduce cancer burden.
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Affiliation(s)
- E. J. Dusic
- Institute of Public Health Genetics, Department of Biostatistics, University of Washington, Seattle, WA, United States
- Correspondence: E. J. Dusic
| | - Tesla Theoryn
- Institute of Public Health Genetics, Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Catharine Wang
- Department of Community Health Sciences, Boston University School of Public Health, Boston, MA, United States
| | - Elizabeth M. Swisher
- Department of Obstetrics and Gynecology, Fred Hutchinson Cancer Center, University of Washington, Seattle, WA, United States
| | - Deborah J. Bowen
- Institute of Public Health Genetics, Department of Biostatistics, University of Washington, Seattle, WA, United States
- Department of Bioethics, University of Washington, Seattle, WA, United States
| | - EDGE Study Team
- Beth Devine, Department of Pharmacy, University of Washington, Seattle, WA, United States
- Barbara Norquist, Department of Obstetrics & Gynecology, University of Washington Medical Center, University of Washington, Seattle, WA, United States
- Brian Shirts, Department of Laboratory Medicine & Pathology, University of Washington Medical Center, University of Washington, Seattle, WA, United States
- Mariebeth Velasquez, Department of Family Medicine, University of Washington Medical Center, University of Washington, Seattle, WA, United States
- Michael Raff, Genomics Institute, MultiCare Health System, Tacoma, WA, United States
- Jeannine M. Brant, Clinical Science & Innovation, Billings Clinic, Billings, MT, United States
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18
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Haidar CE, Crews KR, Hoffman JM, Relling MV, Caudle KE. Advancing Pharmacogenomics from Single-Gene to Preemptive Testing. Annu Rev Genomics Hum Genet 2022; 23:449-473. [PMID: 35537468 PMCID: PMC9483991 DOI: 10.1146/annurev-genom-111621-102737] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.
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Affiliation(s)
- Cyrine E Haidar
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kristine R Crews
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - James M Hoffman
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
- Office of Quality and Safety, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Mary V Relling
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kelly E Caudle
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
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19
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Albalwy F, McDermott JH, Newman WG, Brass A, Davies A. A blockchain-based framework to support pharmacogenetic data sharing. THE PHARMACOGENOMICS JOURNAL 2022; 22:264-275. [PMID: 35869255 DOI: 10.1038/s41397-022-00285-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 06/22/2022] [Accepted: 07/01/2022] [Indexed: 12/11/2022]
Abstract
The successful implementation of pharmacogenetics (PGx) into clinical practice requires patient genomic data to be shared between stakeholders in multiple settings. This creates a number of barriers to widespread adoption of PGx, including privacy concerns related to the storage and movement of identifiable genomic data. Informatic solutions that support secure and equitable data access for genomic data are therefore important to PGx. Here we propose a methodology that uses smart contracts implemented on a blockchain-based framework, PGxChain, to address this issue. The design requirements for PGxChain were identified through a systematic literature review, identifying technical challenges and barriers impeding the clinical implementation of pharmacogenomics. These requirements included security and privacy, accessibility, interoperability, traceability and legal compliance. A proof-of-concept implementation based on Ethereum was then developed that met the design requirements. PGxChain's performance was examined using Hyperledger Caliper for latency, throughput, and transaction success rate. The findings clearly indicate that blockchain technology offers considerable potential to advance pharmacogenetic data sharing, particularly with regard to PGx data security and privacy, large-scale accessibility of PGx data, PGx data interoperability between multiple health care providers and compliance with data-sharing laws and regulations.
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Affiliation(s)
- F Albalwy
- Department of Computer Science, Kilburn Building, University of Manchester, Oxford Road, Manchester, M13 9PL, UK. .,Department of Computer Science, College of Computer Science and Engineering, Taibah University, Madinah, Saudi Arabia. .,Division of Informatics, Imaging and Data Sciences, Stopford Building, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
| | - J H McDermott
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK.,Division of Evolution Infection and Genomics, School of Biological Sciences, University of Manchester, Manchester, UK
| | - W G Newman
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK.,Division of Evolution Infection and Genomics, School of Biological Sciences, University of Manchester, Manchester, UK
| | - A Brass
- Department of Computer Science, Kilburn Building, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.,Division of Informatics, Imaging and Data Sciences, Stopford Building, University of Manchester, Oxford Road, Manchester, M13 9PL, UK
| | - A Davies
- Division of Informatics, Imaging and Data Sciences, Stopford Building, University of Manchester, Oxford Road, Manchester, M13 9PL, UK
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20
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Formea CM, Schultz AJ, Empey PE. Pharmacists Closing Health Disparity Gaps through Pharmacogenomics. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2022. [DOI: 10.1002/jac5.1629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Christine M. Formea
- Intermountain Healthcare, Department of Pharmacy Services Salt Lake City Utah
- Intermountain Precision Genomics, Intermountain Healthcare St. George Utah
| | - April J. Schultz
- Sanford Imagenetics, Sanford Health Sioux Falls South Dakota
- Sanford USD School of Medicine University of South Dakota Sioux Falls South Dakota
| | - Philip E. Empey
- School of Pharmacy University of Pittsburgh Pittsburgh Pennsylvania
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21
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Brown HL, Sherburn IA, Gaff C, Taylor N, Best S. Structured approaches to implementation of clinical genomics: A scoping review. Genet Med 2022; 24:1415-1424. [PMID: 35442192 DOI: 10.1016/j.gim.2022.03.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 03/18/2022] [Accepted: 03/18/2022] [Indexed: 12/23/2022] Open
Abstract
PURPOSE This study aimed to assess the extent to which structured approaches to implementation of clinical genomics, proposed or adapted, are informed by evidence. METHODS A systematic approach was used to identify peer-reviewed articles and gray literature to report on 4 research questions: 1. What structured approaches have been proposed to support implementation? 2. To what extent are the structured approaches informed by evidence? 3. How have structured approaches been deployed in the genomic setting? 4. What are the intended outcomes of the structured approaches? RESULTS A total of 30 unique structured approaches to implementation were reported across 23 peer-reviewed publications and 11 gray literature articles. Most approaches were process models, applied in the preadoption implementation phase, focusing on a "service" outcome. Key findings included a lack of implementation science theory informing the development/implementation of newly designed structured approaches in the genomic setting and a lack of measures to assess implementation effectiveness. CONCLUSION This scoping review identified a significant number of structured approaches developed to inform the implementation of genomic medicine into clinical practice, with limited use of implementation science to support the process. We recommend the use of existing implementation science theory and the expertise of implementation scientists to inform the design of genomic programs being implemented into clinical care.
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Affiliation(s)
- Helen L Brown
- Faculty of Health, Deakin University, Melbourne, Victoria, Australia.
| | - Isabella A Sherburn
- Australian Genomics, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Clara Gaff
- Melbourne Genomics Health Alliance, Walter and Eliza Hall Institute, Melbourne, Victoria, Australia; Department of Paediatrics, Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia
| | - Natalie Taylor
- School of Population Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Stephanie Best
- Australian Genomics, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Australian Institute of Health Innovation (AIHI), Macquarie University, Sydney, New South Wales, Australia
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22
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Voora D, Baye J, McDermaid A, Gowda SN, Wilke RA, Myrmoe AN, Hajek C, Larson EA. SLCO1B1*5 allele is associated with atorvastatin discontinuation and adverse muscle symptoms in the context of routine care. Clin Pharmacol Ther 2022; 111:1075-1083. [PMID: 35034348 PMCID: PMC9303592 DOI: 10.1002/cpt.2527] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 12/13/2021] [Accepted: 12/29/2021] [Indexed: 11/06/2022]
Abstract
SLCO1B1 genotype is known to influence patient adherence to statin therapy, in part by increasing the risk for statin-associated musculoskeletal symptoms (SAMS). The SLCO1B1*5 allele has previously been associated with simvastatin discontinuation and SAMS. Prior analyses of the relationship between SLCO1B1*5 and atorvastatin muscle side effects have been inconclusive due to insufficient power. We now quantify the impact of SLCO1B1*5 on atorvastatin discontinuation and SAMS in a large observational cohort using electronic medical record (EMR) data from a single health care system. In our study cohort (n = 1,627 patients exposed to atorvastatin during the course of routine clinical care), 56% (n = 912 of 1,627 patients) discontinued atorvastatin and 18% (n = 303 of 1,627 patients) developed SAMS. A univariate model revealed that SLCO1B1*5 increased the likelihood that patients would stop atorvastatin during routine care (Odds Ratio 1.2, 95% confidence interval [C.I.]: 1.1 - 1.5, p = 0.04). A multivariate Cox proportional hazards model further demonstrated that this same variant was associated with time to atorvastatin discontinuation (Hazard Ratio 1.2, C.I. 1.1 - 1.4, p = 0.004). Additional time-to-event analyses also revealed that SCLO1B1*5 was associated with SAMS (Hazard Ratio 1.4, C.I. 1.1 - 1.7, p = 0.02). Atorvastatin discontinuation was associated with SAMS (Odds Ratio 1.67, p = 0.0001) in our cohort.
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Affiliation(s)
- Deepak Voora
- Department of Medicine, Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, 27710
| | | | - Adam McDermaid
- Sanford Imagenetics, Sioux Falls, 57105.,Department of Internal Medicine, University of South Dakota, Sanford School of Medicine, Sioux Falls, 57105
| | - Smitha Narayana Gowda
- Department of Internal Medicine, University of South Dakota, Sanford School of Medicine, Sioux Falls, 57105
| | - Russell A Wilke
- Department of Internal Medicine, University of South Dakota, Sanford School of Medicine, Sioux Falls, 57105
| | - Anna Nicole Myrmoe
- Department of Internal Medicine, University of South Dakota, Sanford School of Medicine, Sioux Falls, 57105
| | - Catherine Hajek
- Sanford Imagenetics, Sioux Falls, 57105.,Department of Internal Medicine, University of South Dakota, Sanford School of Medicine, Sioux Falls, 57105
| | - Eric A Larson
- Sanford Imagenetics, Sioux Falls, 57105.,Department of Internal Medicine, University of South Dakota, Sanford School of Medicine, Sioux Falls, 57105
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23
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Liu M, Van Driest SL, Vnencak-Jones CL, Saucier LAG, Roland BP, Gatto CL, Just SL, Weitkamp AO, Peterson JF. Impact of Updating Pharmacogenetic Results: Lessons Learned from the PREDICT Program. J Pers Med 2021; 11:jpm11111051. [PMID: 34834403 PMCID: PMC8617828 DOI: 10.3390/jpm11111051] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/09/2021] [Accepted: 10/13/2021] [Indexed: 12/26/2022] Open
Abstract
Pharmacogenomic (PGx) evidence for selective serotonin reuptake inhibitors (SSRIs) continues to evolve. For sites offering testing, maintaining up-to-date interpretations and implementing new clinical decision support (CDS) driven by existing results creates practical and technical challenges. Vanderbilt University Medical Center initiated panel testing in 2010, added CYP2D6 testing in 2017, and released CDS for SSRIs in 2020. We systematically reinterpreted historic CYP2C19 and CYP2D6 genotypes to update phenotypes to current nomenclature and to launch provider CDS and patient-oriented content for SSRIs. Chart review was conducted to identify and recontact providers caring for patients with current SSRI therapy and new actionable recommendations. A total of 15,619 patients’ PGx results were reprocessed. Of the non-deceased patients reprocessed, 21% (n = 3278) resulted in CYP2C19*1/*17 reinterpretations. Among 289 patients with an actionable recommendation and SSRI medication prescription, 31.8% (n = 92) did not necessitate contact of a clinician, while 43.2% (n = 125) resulted in clinician contacted, and for 25% (n = 72) no appropriate clinician was able to be identified. Maintenance of up-to-date interpretations and recommendations for PGx results over the lifetime of a patient requires continuous effort. Reprocessing is a key strategy for maintenance and expansion of PGx content to be periodically considered and implemented.
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Affiliation(s)
- Michelle Liu
- Department of Pharmacy, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Correspondence:
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (S.L.V.D.); (J.F.P.)
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Cindy L. Vnencak-Jones
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Leigh Ann G. Saucier
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (L.A.G.S.); (B.P.R.); (C.L.G.)
| | - Bartholomew P. Roland
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (L.A.G.S.); (B.P.R.); (C.L.G.)
| | - Cheryl L. Gatto
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (L.A.G.S.); (B.P.R.); (C.L.G.)
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Shari L. Just
- Health IT Decision Support and Knowledge Engineering, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Asli O. Weitkamp
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Josh F. Peterson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (S.L.V.D.); (J.F.P.)
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
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24
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Bright DR, Petry N, Roath E, Gibb T. Engaging pharmacogenomics in pain management and opioid selection. Pharmacogenomics 2021; 22:927-937. [PMID: 34521258 DOI: 10.2217/pgs-2021-0044] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Opioid misuse and mismanagement has been a public health crisis for several years. Pharmacogenomics (PGx) has been proposed as another tool to enhance opioid selection and optimization, with recent studies demonstrating successful implementation and outcomes. However, broad engagement with PGx for opioid management is presently limited. The purpose of this article is to highlight a series of barriers to PGx implementation within the specific context of opioid management. Areas of advancement needed for more robust pharmacogenomic engagement with opioids will be discussed, including clinical and economic research needs, education and training needs, policy and public health considerations, as well as legal and ethical issues. Continuing efforts to address these issues may help to further operationalize PGx toward improving opioid use.
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Affiliation(s)
- David R Bright
- Department of Pharmaceutical Sciences, Ferris State University College of Pharmacy, 220 Ferris Dr, Big Rapids, MI 49307, USA
| | - Natasha Petry
- Department of Pharmacy Practice, College of Health Professions, North Dakota State University, PO Box 6050, Fargo, ND 58108, USA.,Sanford Imagenetics, 1321 W 22nd St, Sioux Falls, SD 57105, USA
| | - Eric Roath
- SpartanNash, 1550 Gezon Parkway, Wyoming, MI 49509, USA
| | - Tyler Gibb
- Department of Medical Ethics, Humanities, & Law, Homer Stryker MD School of Medicine, Western Michigan University, 1000 Oakland Drive, Kalamazoo, MI 49008, USA
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25
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Bishop JR, Huang RS, Brown JT, Mroz P, Johnson SG, Allen JD, Bielinski SJ, England J, Farley JF, Gregornik D, Giri J, Kroger C, Long SE, Luczak T, McGonagle EJ, Ma S, Matey ET, Mandic PK, Moyer AM, Nicholson WT, Petry N, Pawloski PA, Schlichte A, Schondelmeyer SW, Seifert RD, Speedie MK, Stenehjem D, Straka RJ, Wachtl J, Waring SC, Ness BV, Zierhut HA, Aliferis C, Wolf SM, McCarty CA, Jacobson PA. Pharmacogenomics education, research and clinical implementation in the state of Minnesota. Pharmacogenomics 2021; 22:681-691. [PMID: 34137665 DOI: 10.2217/pgs-2021-0058] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Several healthcare organizations across Minnesota have developed formal pharmacogenomic (PGx) clinical programs to increase drug safety and effectiveness. Healthcare professional and student education is strong and there are multiple opportunities in the state for learners to gain workforce skills and develop advanced competency in PGx. Implementation planning is occurring at several organizations and others have incorporated structured utilization of PGx into routine workflows. Laboratory-based and translational PGx research in Minnesota has driven important discoveries in several therapeutic areas. This article reviews the state of PGx activities in Minnesota including educational programs, research, national consortia involvement, technology, clinical implementation and utilization and reimbursement, and outlines the challenges and opportunities in equitable implementation of these advances.
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Affiliation(s)
- Jeffrey R Bishop
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA.,Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - R Stephanie Huang
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Jacob T Brown
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA
| | - Pawel Mroz
- Department of Laboratory Medicine & Pathology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Josiah D Allen
- University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA.,Medigenics Consulting LLC, Minneapolis, MN 55407, USA
| | - Suzette J Bielinski
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Joel F Farley
- Department of Pharmaceutical Care & Health Systems, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - David Gregornik
- Pharmacogenomics Program, Children's Minnesota, Minneapolis, MN 55407, USA
| | - Jyothsna Giri
- Mayo Clinic Center for Individualized Medicine, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Susie E Long
- MHealth Fairview. Acute Care Pharmacy Services, Minneapolis, MN 55455, USA
| | - Tiana Luczak
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA.,Essentia Health, Duluth, MN 55805, USA
| | - Erin J McGonagle
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Sisi Ma
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Eric T Matey
- Department of Pharmacy, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | - Pinar K Mandic
- Department of Finance, University of Minnesota Carlson School of Management, Minneapolis, MN 55455, USA
| | - Ann M Moyer
- Department of Laboratory Medicine & Pathology, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | - Wayne T Nicholson
- Department of Anesthesiology & Perioperative Medicine, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | - Natasha Petry
- Sanford Health Imagenetics, Sioux Falls, SD 57105, USA.,Department of Pharmacy Practice, North Dakota State University College of Health Professions, Fargo, ND 58108, USA
| | | | | | - Stephen W Schondelmeyer
- Department of Pharmaceutical Care & Health Systems, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Randall D Seifert
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA
| | - Marilyn K Speedie
- Department of Medicinal Chemistry, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - David Stenehjem
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA
| | - Robert J Straka
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Jason Wachtl
- Geritom Medical, Inc, Bloomington, MN 55438, USA
| | | | - Brian Van Ness
- Department of Genetics, Cell Biology & Development, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Heather A Zierhut
- Department of Genetics, Cell Biology & Development, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Constantin Aliferis
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Susan M Wolf
- Law School, Medical School, Consortium on Law & Values in Health, Environment & the Life Sciences, University of Minnesota, Minneapolis, MN 55455, USA
| | - Catherine A McCarty
- Department of Family Medicine & Biobehavioral Health, University of Minnesota Medical School, Duluth, MN 55812, USA
| | - Pamala A Jacobson
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
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26
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Luzum JA, Petry N, Taylor AK, Van Driest SL, Dunnenberger HM, Cavallari LH. Moving Pharmacogenetics Into Practice: It's All About the Evidence! Clin Pharmacol Ther 2021; 110:649-661. [PMID: 34101169 DOI: 10.1002/cpt.2327] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 05/27/2021] [Indexed: 12/19/2022]
Abstract
The evidence for pharmacogenetics has grown rapidly in recent decades. However, the strength of evidence required for the clinical implementation of pharmacogenetics is highly debated. Therefore, the purpose of this review is to summarize different perspectives on the evidence required for the clinical implementation of pharmacogenetics. First, we present two patient cases that demonstrate how knowledge of pharmacogenetic evidence affected their care. Then we summarize resources that curate pharmacogenetic evidence, types of evidence (with an emphasis on randomized controlled trials [RCT]) and their limitations, and different perspectives from implementers, clinicians, and patients. We compare pharmacogenetics to a historical example (i.e., the evidence required for the clinical implementation of pharmacokinetics/therapeutic drug monitoring), and we provide future perspectives on the evidence for pharmacogenetic panels and the need for more education in addition to evidence. Although there are differences in the interpretation of pharmacogenetic evidence across resources, efforts for standardization are underway. Survey data illustrate the value of pharmacogenetic testing from the patient perspective, with their providers seen as key to ensuring maximum benefit from test results. However, clinicians and practice guidelines from medical societies often rely on RCT data to guide treatment decisions, which are not always feasible or ethical in pharmacogenetics. Thus, recognition of other types of evidence to support pharmacogenetic implementation is needed. Among pharmacogenetic implementers, consistent evidence of pharmacogenetic associations is deemed most critical. Ultimately, moving pharmacogenetics into practice will require consideration of multiple stakeholder perspectives, keeping particularly attuned to the voice of the ultimate stakeholder-the patient.
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Affiliation(s)
- Jasmine A Luzum
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA
| | - Natasha Petry
- Department of Pharmacy Practice, College of Health Professions, North Dakota State University, Fargo, North Dakota, USA.,Sanford Imagenetics, Sioux Falls, South Dakota, USA
| | - Annette K Taylor
- Colorado Coagulation, Laboratory Corporation of America Holdings, Englewood, Colorado, USA
| | - Sara L Van Driest
- Departments of Pediatrics and Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
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27
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Kisor DF, Petry NJ, Bright DR. Pharmacogenomics in the United States Community Pharmacy Setting: The Clopidogrel- CYP2C19 Example. Pharmgenomics Pers Med 2021; 14:569-577. [PMID: 34040417 PMCID: PMC8140945 DOI: 10.2147/pgpm.s224894] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 04/26/2021] [Indexed: 12/20/2022] Open
Abstract
Pharmacogenomics (PGx) is expanding across health-care practice settings, including the community pharmacy. In the United States, models of implementation of PGx in the community pharmacy have described independent services and those layered on to medication therapy management. The drug-gene pair of clopidogrel-CYP2C19 has been a focus of implementation of PGx in community pharmacy and serves as an example of the evolution of the application of drug-gene interaction information to help optimize drug therapy. Expanded information related to this drug-gene pair has been provided by the US Food and Drug Administration and clinical PGx guidelines have and continue to be updated to support clinical decision-making. Most recently direct-to-consumer (DTC) PGx has resulted in patient generated sample collection and submission to a genetic testing-related company for analysis, with reporting of genotype and related phenotype information directly to the patient without a health-care professional guiding or even being involved in the process. The DTC testing approach needs to be considered in the development or modification of PGx service models in the community pharmacy setting. The example of clopidogrel-CYP2C19 is discussed and current models of PGx implementation in the community pharmacy in the United States are presented. New approaches to PGx services are offered as implementation continues to evolve and may now include DTC information.
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Affiliation(s)
- David F Kisor
- Manchester University, Department of Pharmaceutical Sciences and Pharmacogenomics, Fort Wayne, IN, USA
| | - Natasha J Petry
- North Dakota State University, College of Health Professions, Department of Pharmacy Practice, Fargo, ND, USA
- Sanford Imagenetics, Sioux Falls, ND, USA
| | - David R Bright
- Ferris State University, Department of Pharmaceutical Sciences, Big Rapids, MI, USA
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28
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Roberts MC, Spees LP, Freedman AN, Klein WMP, Prabhu Das I, Butler EN, de Moor JS. Oncologist-Reported Reasons for Not Ordering Multimarker Tumor Panels: Results From a Nationally Representative Survey. JCO Precis Oncol 2021; 5:PO.20.00431. [PMID: 34250411 PMCID: PMC8232803 DOI: 10.1200/po.20.00431] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 03/08/2021] [Accepted: 03/19/2021] [Indexed: 12/14/2022] Open
Abstract
This study examines oncologist-reported reasons for not using multimarker tumor panel testing and the association between these reasons and oncologist-level, facility-level, and patient-mix characteristics. METHODS We used data collected from a nationally representative sample (N = 1,281) of medical oncologists participating in the National Cancer Institute's National Survey of Precision Medicine in Cancer Treatment. RESULTS In addition to testing not being seen as relevant (87%) and no evidence of test utility (77%), the most frequently reported reasons for not ordering a multimarker tumor panel test was difficulty in obtaining sufficient tissue (57%) and using individual gene tests (72%). These reasons were more likely to be reported by oncologists practicing in rural clinics and less likely to be reported by oncologists with an academic affiliation or with access to genetic services such as on-site genetic counselors and internal genetic testing policies. CONCLUSION Modifiable, organizational factors were associated with ordering multimarker tumor panels. Receipt of genomics training and organizational policies related to the use of genomics were associated with lower reporting of barriers to ordering multimarker tumor panels, pointing to potential targets for future studies aimed at increasing appropriate multimarker tumor panel testing in cancer treatment management.
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Affiliation(s)
- Megan C. Roberts
- Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Lisa P. Spees
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Andrew N. Freedman
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
| | - William M. P. Klein
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
| | - Irene Prabhu Das
- Office of the Director, National Institutes of Health, Bethesda, MD
| | - Eboneé N. Butler
- Cancer Prevention Fellowship Program, National Cancer Institute, Bethesda, MD
| | - Janet S. de Moor
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
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29
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Luczak T, Brown SJ, Armbruster D, Hundertmark M, Brown J, Stenehjem D. Strategies and settings of clinical pharmacogenetic implementation: a scoping review of pharmacogenetics programs. Pharmacogenomics 2021; 22:345-364. [PMID: 33829852 DOI: 10.2217/pgs-2020-0181] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Pharmacogenetic (PGx) literature has shown beneficial outcomes in safety, efficacy and cost when evidence-based gene-drug decision making is incorporated into clinical practice. PGx programs with successfully implemented clinical services have been published in a variety of settings including academic health centers and community practice. The primary objective was to systematically scope the literature to characterize the current trends, extent, range and nature of clinical PGx programs. Forty articles representing 19 clinical PGx programs were included in analysis. Most programs are in urban, academic institutions. Education, governance and workflow were commonly described while billing/reimbursement and consent were not. This review provides an overview of current PGx models that can be used as a reference for institutions beginning the implementation process.
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Affiliation(s)
- Tiana Luczak
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA.,Essentia Health, Duluth, MN 55805, USA
| | - Sarah Jane Brown
- Health Sciences Libraries, University of Minnesota, MN 55455, USA
| | - Danielle Armbruster
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Megan Hundertmark
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Jacob Brown
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - David Stenehjem
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
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30
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Christensen KD, Bell M, Zawatsky CLB, Galbraith LN, Green RC, Hutchinson AM, Jamal L, LeBlanc JL, Leonhard JR, Moore M, Mullineaux L, Petry N, Platt DM, Shaaban S, Schultz A, Tucker BD, Van Heukelom J, Wheeler E, Zoltick ES, Hajek C. Precision Population Medicine in Primary Care: The Sanford Chip Experience. Front Genet 2021; 12:626845. [PMID: 33777099 PMCID: PMC7994529 DOI: 10.3389/fgene.2021.626845] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 02/11/2021] [Indexed: 01/10/2023] Open
Abstract
Genetic testing has the potential to revolutionize primary care, but few health systems have developed the infrastructure to support precision population medicine applications or attempted to evaluate its impact on patient and provider outcomes. In 2018, Sanford Health, the nation's largest rural nonprofit health care system, began offering genetic testing to its primary care patients. To date, more than 11,000 patients have participated in the Sanford Chip Program, over 90% of whom have been identified with at least one informative pharmacogenomic variant, and about 1.5% of whom have been identified with a medically actionable predisposition for disease. This manuscript describes the rationale for offering the Sanford Chip, the programs and infrastructure implemented to support it, and evolving plans for research to evaluate its real-world impact.
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Affiliation(s)
- Kurt D Christensen
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States.,Department of Population Medicine, Harvard Medical School, Boston, MA, United States.,Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Megan Bell
- Sanford Health Imagenetics, Sioux Falls, SD, United States
| | - Carrie L B Zawatsky
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States.,Ariadne Labs, Boston, MA, United States
| | - Lauren N Galbraith
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Robert C Green
- Broad Institute of MIT and Harvard, Cambridge, MA, United States.,Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States.,Ariadne Labs, Boston, MA, United States.,Department of Medicine, Harvard Medical School, Boston, MA, United States
| | | | - Leila Jamal
- National Cancer Institute, Bethesda, MD, United States.,Department of Bioethics, National Institutes of Health, Bethesda, MD, United States
| | - Jessica L LeBlanc
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | | | - Michelle Moore
- Sanford Health Imagenetics, Sioux Falls, SD, United States
| | - Lisa Mullineaux
- Mayo Clinic Genomics Laboratory, Rochester, MN, United States
| | - Natasha Petry
- Sanford Health Imagenetics, Fargo, ND, United States.,Department of Pharmacy Practice, North Dakota State University, Fargo, ND, United States
| | - Dylan M Platt
- Sanford Health Imagenetics, Sioux Falls, SD, United States
| | - Sherin Shaaban
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, United States.,ARUP Laboratories, Salt Lake City, UT, United States
| | - April Schultz
- Sanford Health Imagenetics, Sioux Falls, SD, United States.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
| | | | - Joel Van Heukelom
- Sanford Health Imagenetics, Sioux Falls, SD, United States.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
| | | | - Emilie S Zoltick
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Catherine Hajek
- Sanford Health Imagenetics, Sioux Falls, SD, United States.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
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31
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Vassy JL, Gaziano JM, Green RC, Ferguson RE, Advani S, Miller SJ, Chun S, Hage AK, Seo SJ, Majahalme N, MacMullen L, Zimolzak AJ, Brunette CA. Effect of Pharmacogenetic Testing for Statin Myopathy Risk vs Usual Care on Blood Cholesterol: A Randomized Clinical Trial. JAMA Netw Open 2020; 3:e2027092. [PMID: 33270123 PMCID: PMC7716196 DOI: 10.1001/jamanetworkopen.2020.27092] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
IMPORTANCE Nonadherence to statin guidelines is common. The solute carrier organic anion transporter family member 1B1 (SLCO1B1) genotype is associated with simvastatin myopathy risk and is proposed for clinical implementation. The unintended harms of using pharmacogenetic information to guide pharmacotherapy remain a concern for some stakeholders. OBJECTIVE To determine the impact of delivering SLCO1B1 pharmacogenetic results to physicians on the effectiveness of atherosclerotic cardiovascular disease (ASCVD) prevention (measured by low-density lipoprotein cholesterol [LDL-C] levels) and concordance with prescribing guidelines for statin safety and effectiveness. DESIGN, SETTING, AND PARTICIPANTS This randomized clinical trial was performed from December 2015 to July 2019 at 8 primary care practices in the Veterans Affairs Boston Healthcare System. Participants included statin-naive patients with elevated ASCVD risk. Data analysis was performed from October 2019 to September 2020. INTERVENTIONS SLCO1B1 genotyping and results reporting to primary care physicians at baseline (intervention group) vs after 1 year (control group). MAIN OUTCOMES AND MEASURES The primary outcome was the 1-year change in LDL-C level. The secondary outcomes were 1-year concordance with American College of Cardiology-American Heart Association and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for statin therapy and statin-associated muscle symptoms (SAMS). RESULTS Among 408 patients (mean [SD] age, 64.1 [7.8] years; 25 women [6.1%]), 193 were randomized to the intervention group and 215 were randomized to the control group. Overall, 120 participants (29%) had a SLCO1B1 genotype indicating increased simvastatin myopathy risk. Physicians offered statin therapy to 65 participants (33.7%) in the intervention group and 69 participants (32.1%) in the control group. Compared with patients whose physicians did not know their SLCO1B1 results at baseline, patients whose physicians received the results had noninferior reductions in LDL-C at 12 months (mean [SE] change in LDL-C, -1.1 [1.2] mg/dL in the intervention group and -2.2 [1.3] mg/dL in the control group; difference, -1.1 mg/dL; 90% CI, -4.1 to 1.8 mg/dL; P < .001 for noninferiority margin of 10 mg/dL). The proportion of patients with American College of Cardiology-American Heart Association guideline-concordant statin prescriptions in the intervention group was noninferior to that in the control group (12 patients [6.2%] vs 14 patients [6.5%]; difference, -0.003; 90% CI, -0.038 to 0.032; P < .001 for noninferiority margin of 15%). All patients in both groups were concordant with CPIC guidelines for safe statin prescribing. Physicians documented 2 and 3 cases of SAMS in the intervention and control groups, respectively, none of which was associated with a CPIC guideline-discordant prescription. Among patients with a decreased or poor SLCO1B1 transporter function genotype, simvastatin was prescribed to 1 patient in the control group but none in the intervention group. CONCLUSIONS AND RELEVANCE Clinical testing and reporting of SLCO1B1 results for statin myopathy risk did not result in poorer ASCVD prevention in a routine primary care setting and may have been associated with physicians avoiding simvastatin prescriptions for patients at genetic risk for SAMS. Such an absence of harm should reassure stakeholders contemplating the clinical use of available pharmacogenetic results. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02871934.
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Affiliation(s)
- Jason L. Vassy
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Ariadne Labs, Boston, Massachusetts
| | - J. Michael Gaziano
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Robert C. Green
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Ariadne Labs, Boston, Massachusetts
| | - Ryan E. Ferguson
- VA Boston Healthcare System, Boston, Massachusetts
- Department of General Internal Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | | | | | - Sojeong Chun
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | - Anthony K. Hage
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | - Soo-Ji Seo
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | | | | | - Andrew J. Zimolzak
- VA Boston Healthcare System, Boston, Massachusetts
- Baylor College of Medicine, Houston, Texas
- Michael E. DeBakey VA Medical Center, Houston, Texas
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Using Personal Genomic Data within Primary Care: A Bioinformatics Approach to Pharmacogenomics. Genes (Basel) 2020; 11:genes11121443. [PMID: 33266138 PMCID: PMC7761137 DOI: 10.3390/genes11121443] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 11/25/2020] [Accepted: 11/27/2020] [Indexed: 12/14/2022] Open
Abstract
One application of personalized medicine is the tailoring of medication to the individual, so that the medication will have the highest chance of success. In order to individualize medication, one must have a complete inventory of all current pharmaceutical compounds (a detailed formulary) combined with pharmacogenetic datasets, the genetic makeup of the patient, their (medical) family history and other health-related data. For healthcare professionals to make the best use of this information, it must be visualized in a way that makes the most medically relevant data accessible for their decision-making. Similarly, to enable bioinformatics analysis of these data, it must be prepared and provided through an interface for controlled computational analysis. Due to the high degree of personal information gathered for such initiatives, privacy-sensitive implementation choices and ethical standards are paramount. The Personal Genetic Locker project provides an approach to enable the use of personal genomic data in primary care. In this paper, we provide a description of the Personal Genetic Locker project and show its utility through a use case based on open standards, which is illustrated by the 4MedBox system.
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Baye JF, Petry NJ, Jacobson SL, Moore MM, Tucker B, Shaaban S, Massmann AK, Clark NM, Schultz AJ. Malignant hyperthermia susceptibility: utilization of genetic results in an electronic medical record to increase safety. Pharmacogenomics 2020; 21:1207-1215. [PMID: 33118445 DOI: 10.2217/pgs-2020-0088] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
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.
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Affiliation(s)
- Jordan F Baye
- Sanford Health, Imagenetics, Sioux Falls, SD 57105, USA.,Department of Pharmacy Practice, South Dakota State University College of Pharmacy & Allied Health Professions, Brookings, SD 57006, USA.,Department of Internal Medicine, University of South Dakota Sanford School of Medicine, Vermillion, SD, 57069, USA
| | - Natasha J Petry
- Sanford Health, Imagenetics, Sioux Falls, SD 57105, USA.,Department of Pharmacy Practice, North Dakota State University College of Health Professions, Fargo, ND 58108, USA
| | - Shauna L Jacobson
- Department of Anesthesiology, Sanford Health, Sioux Falls, SD 57117, USA
| | | | | | - Sherin Shaaban
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT 84108, USA
| | - Amanda K Massmann
- Sanford Health, Imagenetics, Sioux Falls, SD 57105, USA.,Department of Internal Medicine, University of South Dakota Sanford School of Medicine, Vermillion, SD, 57069, USA
| | | | - April J Schultz
- Sanford Health, Imagenetics, Sioux Falls, SD 57105, USA.,Department of Internal Medicine, University of South Dakota Sanford School of Medicine, Vermillion, SD, 57069, USA
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