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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 DOI: 10.1038/s41431-024-01567-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [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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2
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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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3
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Padmanabhan S, du Toit C, Dominiczak AF. Cardiovascular precision medicine - A pharmacogenomic perspective. CAMBRIDGE PRISMS. PRECISION MEDICINE 2023; 1:e28. [PMID: 38550953 PMCID: PMC10953758 DOI: 10.1017/pcm.2023.17] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 05/24/2023] [Accepted: 06/12/2023] [Indexed: 05/16/2024]
Abstract
Precision medicine envisages the integration of an individual's clinical and biological features obtained from laboratory tests, imaging, high-throughput omics and health records, to drive a personalised approach to diagnosis and treatment with a higher chance of success. As only up to half of patients respond to medication prescribed following the current one-size-fits-all treatment strategy, the need for a more personalised approach is evident. One of the routes to transforming healthcare through precision medicine is pharmacogenomics (PGx). Around 95% of the population is estimated to carry one or more actionable pharmacogenetic variants and over 75% of adults over 50 years old are on a prescription with a known PGx association. Whilst there are compelling examples of pharmacogenomic implementation in clinical practice, the case for cardiovascular PGx is still evolving. In this review, we shall summarise the current status of PGx in cardiovascular diseases and look at the key enablers and barriers to PGx implementation in clinical practice.
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Affiliation(s)
- Sandosh Padmanabhan
- BHF Glasgow Cardiovascular Research Centre, School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Clea du Toit
- BHF Glasgow Cardiovascular Research Centre, School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Anna F. Dominiczak
- BHF Glasgow Cardiovascular Research Centre, School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
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4
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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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5
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Smith DM, Wake DT, Dunnenberger HM. Pharmacogenomic Clinical Decision Support: A Scoping Review. Clin Pharmacol Ther 2023; 113:803-815. [PMID: 35838358 DOI: 10.1002/cpt.2711] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 07/10/2022] [Indexed: 11/06/2022]
Abstract
Clinical decision support (CDS) is often cited as an essential part of pharmacogenomics (PGx) implementations. A multitude of strategies are available; however, it is unclear which strategies are effective and which metrics are used to quantify clinical utility. The objective of this scoping review was to aggregate previous studies into a cohesive depiction of the current state of PGx CDS implementations and identify areas for future research on PGx CDS. Articles were included if they (i) described electronic CDS tools for PGx and (ii) reported metrics related to PGx CDS. Twenty of 3,449 articles were included and provided data on PGx CDS metrics from 15 institutions, with 93% of programs located at academic medical centers. The most common tools in CDS implementations were interruptive post-test alerts. Metrics for clinical response and alert response ranged from 12-73% and 21-98%, respectively. Few data were found on changes in metrics over time and measures that drove the evolution of CDS systems. Relatively few data were available regarding support of optimal approaches for PGx CDS. Post-test alerts were the most widely studied approach, and their effectiveness varied greatly. Further research on the usability, effectiveness, and optimization of CDS tools is needed.
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Affiliation(s)
- D Max Smith
- MedStar Health, Columbia, Maryland, USA.,Georgetown University Medical Center, Washington, District of Columbia, USA
| | - Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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6
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Obeng AO, Scott SA, Kaszemacher T, Ellis SB, Mejia A, Gomez A, Nadukuru R, Abul-Husn NS, Vega A, Waite E, Gottesman O, Cho J, Bottinger EP. Prescriber Adoption of SLCO1B1 Genotype-Guided Simvastatin Clinical Decision Support in a Clinical Pharmacogenetics Program. Clin Pharmacol Ther 2023; 113:321-327. [PMID: 36372942 DOI: 10.1002/cpt.2773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 10/08/2022] [Indexed: 11/15/2022]
Abstract
Pharmacogenetic implementation programs are increasingly feasible due to the availability of clinical guidelines for implementation research. The utilization of these resources has been reported with selected drug-gene pairs; however, little is known about how prescribers respond to pharmacogenetic recommendations for statin therapy. We prospectively assessed prescriber interaction with point-of-care clinical decision support (CDS) to guide simvastatin therapy for a diverse cohort of primary care patients enrolled in a clinical pharmacogenetics program. Of the 1,639 preemptively genotyped patients, 298 (18.2%) had an intermediate function (IF) OATP1B1 phenotype and 25 (1.53%) had a poor function (PF) phenotype, predicted by a common single nucleotide variant in the SLCO1B1 gene (c.521T>C; rs4149056). Clinicians were presented with CDS when simvastatin was prescribed for patients with IF or PF through the electronic health record. Importantly, 64.2% of the CDS deployed at the point-of-care was accepted by the prescribers and resulted in prescription changes. Statin intensity was found to significantly influence prescriber adoption of the pharmacogenetic-guided CDS, whereas patient gender or race, prescriber type, or pharmacogenetic training status did not significantly influence adoption. This study demonstrates that primary care providers readily adopt pharmacogenetic information to guide statin therapy for the majority of patients with preemptive genotype data.
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Affiliation(s)
- Aniwaa Owusu Obeng
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Pharmacy Department, The Mount Sinai Hospital, New York, New York, USA.,Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Stuart A Scott
- Department of Pathology, Stanford University, Stanford, California, USA.,Clinical Genomics Laboratory, Stanford Health Care, Palo Alto, California, USA
| | - Tom Kaszemacher
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Stephen B Ellis
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ana Mejia
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Alanna Gomez
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Rajiv Nadukuru
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Noura S Abul-Husn
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,23andMe Inc., Sunnyvale, California, USA
| | - Aida Vega
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Mount Sinai Faculty Practice Associates, Primary Care Program, The Mount Sinai Health system, New York, New York, USA
| | - Eva Waite
- Mount Sinai Faculty Practice Associates, Primary Care Program, The Mount Sinai Health system, New York, New York, USA
| | - Omri Gottesman
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Empirico Inc., San Diego, California, USA
| | - Judy Cho
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Erwin P Bottinger
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Digital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany
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7
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Cavallari LH, Pratt VM. Building Evidence for Clinical Use of Pharmacogenomics and Reimbursement for Testing. Clin Lab Med 2022; 42:533-546. [PMID: 36368780 PMCID: PMC9896522 DOI: 10.1016/j.cll.2022.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, PO Box 100486, Gainesville, FL 32610-0486, USA.
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8
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Fragala MS, Shaman JA, Lorenz RA, Goldberg SE. Role of Pharmacogenomics in Comprehensive Medication Management: Considerations for Employers. Popul Health Manag 2022; 25:753-762. [PMID: 36301527 DOI: 10.1089/pop.2022.0075] [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: 12/31/2022] Open
Abstract
Rising prescription costs, poor medication adherence, and safety issues pose persistent challenges to employer-sponsored health care plans and their beneficiaries. Comprehensive medication management (CMM), a patient-centered approach to medication optimization, enriched by pharmacogenomics (PGx), has been shown to improve the efficacy and safety of pharmaceutical regimens. This has contributed to improved health care outcomes, reduced costs of treatments, better adherence, shorter durations of treatment, and fewer adverse effects from drug therapy. Despite compelling clinical and economic evidence to justify the application of CMM guided by PGx, implementation in clinical settings remains sparse; notable barriers include limited physician adoption and health insurance coverage. Ultimately, these challenges may be overcome through comprehensive programs that include clinical decision support systems and education through employer-sponsored population health management channels to the benefit of the employees, employers, health care providers, and health care systems. This article discusses benefits, considerations, and barriers of scalable PGx-enriched CMM programs in the context of self-insured employers.
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9
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Abstract
Over the past decade, pharmacogenetic testing has emerged in clinical practice to guide selected cardiovascular therapies. The most common implementation in practice is CYP2C19 genotyping to predict clopidogrel response and assist in selecting antiplatelet therapy after percutaneous coronary intervention. Additional examples include genotyping to guide warfarin dosing and statin prescribing. Increasing evidence exists on outcomes with genotype-guided cardiovascular therapies from multiple randomized controlled trials and observational studies. Pharmacogenetic evidence is accumulating for additional cardiovascular medications. However, data for many of these medications are not yet sufficient to support the use of genotyping for drug prescribing. Ultimately, pharmacogenetics might provide a means to individualize drug regimens for complex diseases such as heart failure, in which the treatment armamentarium includes a growing list of medications shown to reduce morbidity and mortality. However, sophisticated analytical approaches are likely to be necessary to dissect the genetic underpinnings of responses to drug combinations. In this Review, we examine the evidence supporting pharmacogenetic testing in cardiovascular medicine, including that available from several clinical trials. In addition, we describe guidelines that support the use of cardiovascular pharmacogenetics, provide examples of clinical implementation of genotype-guided cardiovascular therapies and discuss opportunities for future growth of the field.
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10
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Keeling NJ, Dunn TJ, Bentley JP, Ramachandran S, Hoffman JM, Rosenthal M. Approaches to assessing the provider experience with clinical pharmacogenomic information: a scoping review. Genet Med 2021; 23:1589-1603. [PMID: 33927377 DOI: 10.1038/s41436-021-01186-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 04/11/2021] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Barriers to the implementation of pharmacogenomics in clinical practice have been thoroughly discussed over the past decade. METHODS The objective of this scoping review was to characterize the peer-reviewed literature surrounding the experiences and actions of prescribers, pharmacists, or genetic counselors when using pharmacogenomic information in real-world or hypothetical research settings. RESULTS A total of 33 studies were included in the scoping review. The majority of studies were conducted in the United States (70%), used quantitative or mixed methods (79%) with physician or pharmacist respondents (100%). The qualitative content analysis revealed five major methodological approaches: hypothetical clinical case scenarios, real-world studies evaluating prescriber response to recommendations or alerts, cross-sectional quantitative surveys, cross-sectional qualitative surveys/interviews, and a quasi-experimental real-world study. CONCLUSION The findings of this scoping review can guide further research on the factors needed to successfully integrate pharmacogenomics into clinical care.
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Affiliation(s)
- Nicholas J Keeling
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
| | - Tyler J Dunn
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA.
| | - John P Bentley
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
| | - Sujith Ramachandran
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
| | - James M Hoffman
- Department of Pharmaceutical Sciences and Office of Quality and Patient Care, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Meagen Rosenthal
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
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11
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Lee CR, Thomas CD, Beitelshees AL, Tuteja S, Empey PE, Lee JC, Limdi NA, Duarte JD, Skaar TC, Chen Y, Cook KJ, Coons JC, Dillon C, Franchi F, Giri J, Gong Y, Kreutz RP, McDonough CW, Stevenson JM, Weck KE, Angiolillo DJ, Johnson JA, Stouffer GA, Cavallari LH. Impact of the CYP2C19*17 Allele on Outcomes in Patients Receiving Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention. Clin Pharmacol Ther 2020; 109:705-715. [PMID: 32897581 DOI: 10.1002/cpt.2039] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 08/18/2020] [Indexed: 01/03/2023]
Abstract
Genotyping for CYP2C19 no function alleles to guide antiplatelet therapy after percutaneous coronary intervention (PCI) improves clinical outcomes. Although results for the increased function CYP2C19*17 allele are also reported, its clinical relevance in this setting remains unclear. A collaboration across nine sites examined antiplatelet therapy prescribing and clinical outcomes in 3,342 patients after implementation of CYP2C19-guided antiplatelet therapy. Risk of major atherothrombotic and bleeding events over 12 months after PCI were compared across cytochrome P450 2C19 isozyme (CYP2C19) metabolizer phenotype and antiplatelet therapy groups by proportional hazards regression. Clopidogrel was prescribed to a similar proportion of CYP2C19 normal (84.5%), rapid (82.9%), and ultrarapid metabolizers (80.6%) (P = 0.360). Clopidogrel-treated normal metabolizers (20.4 events/100 patient-years; adjusted hazard ratio (HR) 1.00, 95% confidence interval (CI), 0.75-1.33, P = 0.993) and clopidogrel-treated rapid or ultrarapid metabolizers (19.1 events/100 patient-years; adjusted HR 0.95, 95% CI, 0.69-1.30, P = 0.734) exhibited no difference in major atherothrombotic events compared with patients treated with prasugrel or ticagrelor (17.6 events/100 patient-years). In contrast, clopidogrel-treated intermediate and poor metabolizers exhibited significantly higher atherothrombotic event risk compared with prasugrel/ticagrelor-treated patients (adjusted HR 1.56, 95% CI, 1.12-2.16, P = 0.008). When comparing clopidogrel-treated rapid or ultrarapid metabolizers to normal metabolizers, no difference in atherothrombotic (adjusted HR 0.97, 95% CI, 0.73-1.29, P = 0.808) or bleeding events (adjusted HR 1.34, 95% CI, 0.83-2.17, P = 0.224) were observed. In a real-world setting of genotype-guided antiplatelet therapy, the CYP2C19*17 allele did not significantly impact post-PCI prescribing decisions or clinical outcomes. These results suggest the CYP2C19 *1/*17 and *17/*17 genotypes have limited clinical utility to guide antiplatelet therapy after PCI.
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Affiliation(s)
- Craig R Lee
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Cameron D Thomas
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | | | - Sony Tuteja
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Philip E Empey
- School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - James C Lee
- Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Nita A Limdi
- University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Julio D Duarte
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Todd C Skaar
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Yiqing Chen
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Kelsey J Cook
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - James C Coons
- School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Chrisly Dillon
- University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Francesco Franchi
- Department of Medicine, Division of Cardiology, University of Florida, Jacksonville, Florida, USA
| | - Jay Giri
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Rolf P Kreutz
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Caitrin W McDonough
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - James M Stevenson
- School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Karen E Weck
- Division of Cardiology and McAllister Heart Institute, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Dominick J Angiolillo
- Department of Medicine, Division of Cardiology, University of Florida, Jacksonville, Florida, USA
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - George A Stouffer
- Division of Cardiology and McAllister Heart Institute, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
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Johnson KB, Clayton EW, Starren J, Peterson J. The Implementation Chasm Hindering Genome-informed Health Care. THE JOURNAL OF LAW, MEDICINE & ETHICS : A JOURNAL OF THE AMERICAN SOCIETY OF LAW, MEDICINE & ETHICS 2020; 48:119-125. [PMID: 32342791 PMCID: PMC7395963 DOI: 10.1177/1073110520916999] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The promises of precision medicine are often heralded in the medical and lay literature, but routine integration of genomics in clinical practice is still limited. While the "last mile' infrastructure to bring genomics to the bedside has been demonstrated in some healthcare settings, a number of challenges remain - both in the receptivity of today's health system and in its technical and educational readiness to respond to this evolution in care. To improve the impact of genomics on health and disease management, we will need to integrate both new knowledge and new care processes into existing workflows. This change will be onerous and time-consuming, but hopefully valuable to the provision of high quality, economically feasible care worldwide.
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Affiliation(s)
- Kevin B Johnson
- Kevin B. Johnson, M.D., M.S., is Cornelius Vanderbilt Professor and Chair of Biomedical Informatics, with a joint appointment in the Department of Pediatrics at Vanderbilt University Medical Center. He received his M.D. from Johns Hopkins Hospital in Baltimore and his M.S. in Medical Informatics from Stanford University in 1992. Ellen Wright Clayton, M.D., J.D., is the Craig-Weaver Professor of Pediatrics, Professor of Health Policy in the Center for Biomedical Ethics and Society at Vanderbilt University Medical Center, and Professor of Law at Vanderbilt University. She has been studying the ethical, legal, and social implications of genetics research and its translation to the clinic for many years. She is currently a PI of LawSeq as well as GetPreCiSe, a Center of Excellence in ELSI Research focused on genetic privacy and identity, and has been an investigator in the eMERGE Network since its inception. Justin Starren, M.D., M.S., Ph.D., is Professor of Preventive Medicine and Medical Social Sciences and Chief of the Division of Health and Biomedical Informatics at the Northwestern University Feinberg School of Medicine. He received his M.D. and M.S. in Immunogenetics from Washington University in St. Louis in 1987, and his Ph.D. in Biomedical Informatics from Columbia University in 1997. Josh Peterson, M.D., M.P.H., is an Associate Professor of Biomedical Informatics and Medicine at Vanderbilt University Medical Center. He received his M.D. from Vanderbilt University in 1997 and his M.P.H. from Harvard University School of Public Health in 2002
| | - Ellen Wright Clayton
- Kevin B. Johnson, M.D., M.S., is Cornelius Vanderbilt Professor and Chair of Biomedical Informatics, with a joint appointment in the Department of Pediatrics at Vanderbilt University Medical Center. He received his M.D. from Johns Hopkins Hospital in Baltimore and his M.S. in Medical Informatics from Stanford University in 1992. Ellen Wright Clayton, M.D., J.D., is the Craig-Weaver Professor of Pediatrics, Professor of Health Policy in the Center for Biomedical Ethics and Society at Vanderbilt University Medical Center, and Professor of Law at Vanderbilt University. She has been studying the ethical, legal, and social implications of genetics research and its translation to the clinic for many years. She is currently a PI of LawSeq as well as GetPreCiSe, a Center of Excellence in ELSI Research focused on genetic privacy and identity, and has been an investigator in the eMERGE Network since its inception. Justin Starren, M.D., M.S., Ph.D., is Professor of Preventive Medicine and Medical Social Sciences and Chief of the Division of Health and Biomedical Informatics at the Northwestern University Feinberg School of Medicine. He received his M.D. and M.S. in Immunogenetics from Washington University in St. Louis in 1987, and his Ph.D. in Biomedical Informatics from Columbia University in 1997. Josh Peterson, M.D., M.P.H., is an Associate Professor of Biomedical Informatics and Medicine at Vanderbilt University Medical Center. He received his M.D. from Vanderbilt University in 1997 and his M.P.H. from Harvard University School of Public Health in 2002
| | - Justin Starren
- Kevin B. Johnson, M.D., M.S., is Cornelius Vanderbilt Professor and Chair of Biomedical Informatics, with a joint appointment in the Department of Pediatrics at Vanderbilt University Medical Center. He received his M.D. from Johns Hopkins Hospital in Baltimore and his M.S. in Medical Informatics from Stanford University in 1992. Ellen Wright Clayton, M.D., J.D., is the Craig-Weaver Professor of Pediatrics, Professor of Health Policy in the Center for Biomedical Ethics and Society at Vanderbilt University Medical Center, and Professor of Law at Vanderbilt University. She has been studying the ethical, legal, and social implications of genetics research and its translation to the clinic for many years. She is currently a PI of LawSeq as well as GetPreCiSe, a Center of Excellence in ELSI Research focused on genetic privacy and identity, and has been an investigator in the eMERGE Network since its inception. Justin Starren, M.D., M.S., Ph.D., is Professor of Preventive Medicine and Medical Social Sciences and Chief of the Division of Health and Biomedical Informatics at the Northwestern University Feinberg School of Medicine. He received his M.D. and M.S. in Immunogenetics from Washington University in St. Louis in 1987, and his Ph.D. in Biomedical Informatics from Columbia University in 1997. Josh Peterson, M.D., M.P.H., is an Associate Professor of Biomedical Informatics and Medicine at Vanderbilt University Medical Center. He received his M.D. from Vanderbilt University in 1997 and his M.P.H. from Harvard University School of Public Health in 2002
| | - Josh Peterson
- Kevin B. Johnson, M.D., M.S., is Cornelius Vanderbilt Professor and Chair of Biomedical Informatics, with a joint appointment in the Department of Pediatrics at Vanderbilt University Medical Center. He received his M.D. from Johns Hopkins Hospital in Baltimore and his M.S. in Medical Informatics from Stanford University in 1992. Ellen Wright Clayton, M.D., J.D., is the Craig-Weaver Professor of Pediatrics, Professor of Health Policy in the Center for Biomedical Ethics and Society at Vanderbilt University Medical Center, and Professor of Law at Vanderbilt University. She has been studying the ethical, legal, and social implications of genetics research and its translation to the clinic for many years. She is currently a PI of LawSeq as well as GetPreCiSe, a Center of Excellence in ELSI Research focused on genetic privacy and identity, and has been an investigator in the eMERGE Network since its inception. Justin Starren, M.D., M.S., Ph.D., is Professor of Preventive Medicine and Medical Social Sciences and Chief of the Division of Health and Biomedical Informatics at the Northwestern University Feinberg School of Medicine. He received his M.D. and M.S. in Immunogenetics from Washington University in St. Louis in 1987, and his Ph.D. in Biomedical Informatics from Columbia University in 1997. Josh Peterson, M.D., M.P.H., is an Associate Professor of Biomedical Informatics and Medicine at Vanderbilt University Medical Center. He received his M.D. from Vanderbilt University in 1997 and his M.P.H. from Harvard University School of Public Health in 2002
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Tuteja S, Glick H, Matthai W, Nachamkin I, Nathan A, Monono K, Carcuffe C, Maslowski K, Chang G, Kobayashi T, Anwaruddin S, Hirshfeld J, Wilensky RL, Herrmann HC, Kolansky DM, Rader DJ, Giri J. Prospective CYP2C19 Genotyping to Guide Antiplatelet Therapy Following Percutaneous Coronary Intervention: A Pragmatic Randomized Clinical Trial. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2020; 13:e002640. [PMID: 31928229 DOI: 10.1161/circgen.119.002640] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND CYP2C19 loss-of-function alleles impair clopidogrel effectiveness after percutaneous coronary intervention, but the clinical impact of implementing CYP2C19 genotyping in a real-world setting is unknown. The purpose of the study was to determine whether returning CYP2C19 genotype results along with genotype-guided pharmacotherapy recommendations using a rapid turnaround test would change antiplatelet prescribing following percutaneous coronary intervention.The primary outcome was the rate of prasugrel or ticagrelor prescribing in each arm. Secondary outcomes included agreement to the genotype-guided recommendations. METHODS At the time of percutaneous coronary intervention, participants were randomly assigned to prospective rapid point-of-care genotyping of CYP2C19 major alleles (*2, *3, *17) via salivary swab (genotyped group) or no genotyping (usual care) to guide antiplatelet drug selection. Interventional cardiologists at 2 cardiac catheterization laboratories within the same health system were provided genotype information along with genotype-guided pharmacotherapy recommendations. RESULTS A total of 504 participants were randomized, 249 to the genotyped and 255 to the usual care group. The participants were primarily men (73%); age, 63±10 years; and 50% had acute coronary syndromes. In the genotyped group, 28% were carriers of loss-of-function alleles (*2, *3). The use of prasugrel or ticagrelor was significantly higher in the genotyped group compared with the usual care group (30% versus 21%; odds ratio, 1.60 [95% CI, 1.07-2.42]; P=0.03). Within the genotyped group, 53% of loss-of-function allele carriers were started on prasugrel/ticagrelor, while 47% were started on clopidogrel. CONCLUSIONS In a randomized controlled trial of clinical CYP2C19 genotyping implementation, pharmacogenetic test results significantly influenced antiplatelet drug prescribing; however, almost half of CYP2C19 loss-of-function carriers continued to receive clopidogrel. Interventional cardiologists consider both clinical and genetic factors when selecting antiplatelet therapy following percutaneous coronary intervention. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique Identifier: NCT02508116.
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Affiliation(s)
- Sony Tuteja
- Department of Medicine, Division of Translational Medicine and Human Genetics (S.T., K. Monono, D.J.R.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Henry Glick
- Department of Biostatistics and Epidemiology (H.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - William Matthai
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Irving Nachamkin
- Department of Pathology and Laboratory Medicine (I.N.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Ashwin Nathan
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia.,Penn Cardiovascular Outcomes, Quality, and Evaluative Research Center, Leonard Davis Institute of Health Economics (A.N., T.K., R.L.W., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Karen Monono
- Department of Medicine, Division of Translational Medicine and Human Genetics (S.T., K. Monono, D.J.R.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Craig Carcuffe
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Karen Maslowski
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Gene Chang
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Taisei Kobayashi
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia.,Penn Cardiovascular Outcomes, Quality, and Evaluative Research Center, Leonard Davis Institute of Health Economics (A.N., T.K., R.L.W., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Saif Anwaruddin
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - John Hirshfeld
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Robert L Wilensky
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia.,Penn Cardiovascular Outcomes, Quality, and Evaluative Research Center, Leonard Davis Institute of Health Economics (A.N., T.K., R.L.W., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Howard C Herrmann
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Daniel M Kolansky
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Daniel J Rader
- Department of Medicine, Division of Translational Medicine and Human Genetics (S.T., K. Monono, D.J.R.), University of Pennsylvania Perelman School of Medicine, Philadelphia.,Department of Genetics (D.J.R.), University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Jay Giri
- Cardiovascular Medicine Division (W.M., A.N., C.C., K. Maslowski, G.C., T.K., S.A., J.H., R.L.W., H.C.H., D.M.K., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia.,Penn Cardiovascular Outcomes, Quality, and Evaluative Research Center, Leonard Davis Institute of Health Economics (A.N., T.K., R.L.W., J.G.), University of Pennsylvania Perelman School of Medicine, Philadelphia
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14
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Herr TM, Peterson JF, Rasmussen LV, Caraballo PJ, Peissig PL, Starren JB. Pharmacogenomic clinical decision support design and multi-site process outcomes analysis in the eMERGE Network. J Am Med Inform Assoc 2020; 26:143-148. [PMID: 30590574 DOI: 10.1093/jamia/ocy156] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Accepted: 11/05/2018] [Indexed: 11/12/2022] Open
Abstract
To better understand the real-world effects of pharmacogenomic (PGx) alerts, this study aimed to characterize alert design within the eMERGE Network, and to establish a method for sharing PGx alert response data for aggregate analysis. Seven eMERGE sites submitted design details and established an alert logging data dictionary. Six sites participated in a pilot study, sharing alert response data from their electronic health record systems. PGx alert design varied, with some consensus around the use of active, post-test alerts to convey Clinical Pharmacogenetics Implementation Consortium recommendations. Sites successfully shared response data, with wide variation in acceptance and follow rates. Results reflect the lack of standardization in PGx alert design. Standards and/or larger studies will be necessary to fully understand PGx impact. This study demonstrated a method for sharing PGx alert response data and established that variation in system design is a significant barrier for multi-site analyses.
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Affiliation(s)
- Timothy M Herr
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Josh F Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Luke V Rasmussen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Pedro J Caraballo
- Department of Medicine and Center for Translational Informatics and Knowledge Management, Mayo Clinic, Rochester, Minnesota, USA
| | - Peggy L Peissig
- Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
| | - Justin B Starren
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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15
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Roden DM, Van Driest SL, Wells QS, Mosley JD, Denny JC, Peterson JF. Opportunities and Challenges in Cardiovascular Pharmacogenomics: From Discovery to Implementation. Circ Res 2019; 122:1176-1190. [PMID: 29700066 DOI: 10.1161/circresaha.117.310965] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
This review will provide an overview of the principles of pharmacogenomics from basic discovery to implementation, encompassing application of tools of contemporary genome science to the field (including areas of apparent divergence from disease-based genomics), a summary of lessons learned from the extensively studied drugs clopidogrel and warfarin, the current status of implementing pharmacogenetic testing in practice, the role of genomics and related tools in the drug development process, and a summary of future opportunities and challenges.
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Affiliation(s)
- Dan M Roden
- From the Department of Medicine (D.M.R., S.L.V.D., Q.S.W., J.D.M., J.C.D., J.F.P.) .,Department of Pharmacology (D.M.R., Q.S.W.).,Department of Biomedical Informatics (D.M.R., J.C.D., J.F.P.)
| | - Sara L Van Driest
- From the Department of Medicine (D.M.R., S.L.V.D., Q.S.W., J.D.M., J.C.D., J.F.P.).,Department of Pediatrics (S.L.V.D.), Vanderbilt University Medical Center, Nashville, TN
| | - Quinn S Wells
- From the Department of Medicine (D.M.R., S.L.V.D., Q.S.W., J.D.M., J.C.D., J.F.P.).,Department of Pharmacology (D.M.R., Q.S.W.)
| | - Jonathan D Mosley
- From the Department of Medicine (D.M.R., S.L.V.D., Q.S.W., J.D.M., J.C.D., J.F.P.)
| | - Joshua C Denny
- From the Department of Medicine (D.M.R., S.L.V.D., Q.S.W., J.D.M., J.C.D., J.F.P.).,Department of Biomedical Informatics (D.M.R., J.C.D., J.F.P.)
| | - Josh F Peterson
- From the Department of Medicine (D.M.R., S.L.V.D., Q.S.W., J.D.M., J.C.D., J.F.P.).,Department of Biomedical Informatics (D.M.R., J.C.D., J.F.P.)
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16
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Shi Y, Graves JA, Garbett SP, Zhou Z, Marathi R, Wang X, Harrell FE, Lasko TA, Denny JC, Roden DM, Peterson JF, Schildcrout JS. A Decision-Theoretic Approach to Panel-Based, Preemptive Genotyping. MDM Policy Pract 2019; 4:2381468319864337. [PMID: 31453360 PMCID: PMC6699004 DOI: 10.1177/2381468319864337] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Accepted: 06/01/2019] [Indexed: 12/22/2022] Open
Abstract
We discuss a decision-theoretic approach to building a panel-based, preemptive
genotyping program. The method is based on findings that a large percentage of
patients are prescribed medications that are known to have pharmacogenetic
associations, and over time, a substantial proportion are prescribed additional
such medication. Preemptive genotyping facilitates genotype-guided therapy at
the time medications are prescribed; panel-based testing allows providers to
reuse previously collected genetic data when a new indication arises. Because it
is cost-prohibitive to conduct panel-based genotyping on all patients, we
describe a three-step approach to identify patients with the highest anticipated
benefit. First, we construct prediction models to estimate the risk of being
prescribed one of the target medications using readily available clinical data.
Second, we use literature-based estimates of adverse event rates, variant allele
frequencies, secular death rates, and costs to construct a discrete event
simulation that estimates the expected benefit of having an individual’s genetic
data in the electronic health record after an indication has occurred. Finally,
we combine medication prescription risk with expected benefit of genotyping once
a medication is indicated to calculate the expected benefit of preemptive
genotyping. For each patient-clinic visit, we calculate this expected benefit
across a range of medications and select patients with the highest expected
benefit overall. We build a proof of concept implementation using a cohort of
patients from a single academic medical center observed from July 2010 through
December 2012. We then apply the results of our modeling strategy to show the
extent to which we can improve clinical and economic outcomes in a cohort
observed from January 2013 through December 2015.
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Affiliation(s)
- Yaping Shi
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - John A Graves
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Shawn P Garbett
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Zilu Zhou
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Ramya Marathi
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Xiaoming Wang
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Frank E Harrell
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Thomas A Lasko
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Joshua C Denny
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Dan M Roden
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Josh F Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
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17
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Roden DM, McLeod HL, Relling MV, Williams MS, Mensah GA, Peterson JF, Van Driest SL. Pharmacogenomics. Lancet 2019; 394:521-532. [PMID: 31395440 PMCID: PMC6707519 DOI: 10.1016/s0140-6736(19)31276-0] [Citation(s) in RCA: 211] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 04/04/2019] [Accepted: 05/16/2019] [Indexed: 02/08/2023]
Abstract
Genomic medicine, which uses DNA variation to individualise and improve human health, is the subject of this Series of papers. The idea that genetic variation can be used to individualise drug therapy-the topic addressed here-is often viewed as within reach for genomic medicine. We have reviewed general mechanisms underlying variability in drug action, the role of genetic variation in mediating beneficial and adverse effects through variable drug concentrations (pharmacokinetics) and drug actions (pharmacodynamics), available data from clinical trials, and ongoing efforts to implement pharmacogenetics in clinical practice.
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Affiliation(s)
- Dan M Roden
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Howard L McLeod
- DeBartolo Family Personalized Medicine Institute, Moffitt Cancer Center, Tampa, FL, USA
| | - Mary V Relling
- Pharmaceutical Department, St Jude Children's Research Hospital, Memphis, TN, USA
| | | | - George A Mensah
- Center for Translation Research and Implementation Science, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Josh F Peterson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sara L Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
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18
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Frequency and clinical outcomes of CYP2C19 genotype-guided escalation and de-escalation of antiplatelet therapy in a real-world clinical setting. Genet Med 2019; 22:160-169. [PMID: 31316169 PMCID: PMC6946839 DOI: 10.1038/s41436-019-0611-1] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 07/08/2019] [Indexed: 12/13/2022] Open
Abstract
Purpose To evaluate the frequency and clinical impact of switches in antiplatelet therapy following implementation of CYP2C19 genotyping after percutaneous coronary intervention (PCI). Methods The frequency of escalation (clopidogrel switched to prasugrel/ticagrelor) and de-escalation (prasugrel/ticagrelor switched to clopidogrel) was evaluated in 1063 PCI patients who underwent CYP2C19 genotyping. Risk of major adverse cardiovascular or cerebrovascular (MACCE) and bleeding events over one-year was evaluated. Results Antiplatelet therapy switches were common (19%), with escalation (101/115: 88%) and de-escalation (77/84: 92%) occurring predominantly in patients with and without a CYP2C19 nonfunctional allele, respectively. Nonfunctional allele carriers initiated and continued on clopidogrel had a significantly higher risk of experiencing either a MACCE or bleeding event compared to those escalated to prasugrel/ticagrelor (52 vs. 19 events/100 patient-years; adjusted hazard ratio [HR] 2.89 [1.44–6.13], p=0.003). Patients without a nonfunctional allele de-escalated to clopidogrel had no difference in risk compared to those initiated and continued on prasugrel/ticagrelor (21 vs. 19 events/100 patient-years; adjusted HR 1.13 [0.51–2.34], p=0.751). Conclusions CYP2C19-guided escalation and de-escalation is common in a real-world setting. Continuation of clopidogrel in nonfunctional allele carriers is associated with adverse outcomes. De-escalation to clopidogrel in patients without a nonfunctional allele appears safe and warrants prospective study.
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Lee CR, Sriramoju VB, Cervantes A, Howell LA, Varunok N, Madan S, Hamrick K, Polasek MJ, Lee JA, Clarke M, Cicci JD, Weck KE, Stouffer GA. Clinical Outcomes and Sustainability of Using CYP2C19 Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2019; 11:e002069. [PMID: 29615454 DOI: 10.1161/circgen.117.002069] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Accepted: 02/05/2018] [Indexed: 01/10/2023]
Abstract
BACKGROUND CYP2C19 loss-of-function (LOF) alleles impair clopidogrel effectiveness after percutaneous coronary intervention. The feasibility, sustainability, and clinical impact of using CYP2C19 genotype-guided dual antiplatelet therapy (DAPT) selection in practice remains unclear. METHODS A single-center observational study was conducted in 1193 patients who underwent percutaneous coronary intervention and received DAPT after implementation of an algorithm that recommends CYP2C19 testing in high-risk patients and alternative DAPT (prasugrel or ticagrelor) in LOF allele carriers. The frequency of genotype testing and alternative DAPT selection were the primary implementation end points. Risk of major adverse cardiovascular or cerebrovascular and clinically significant bleeding events over 12 months were compared across genotype and DAPT groups by proportional hazards regression. RESULTS CYP2C19 genotype was obtained in 868 (72.8%) patients. Alternative DAPT was prescribed in 186 (70.7%) LOF allele carriers. CYP2C19 testing (P<0.001) and alternative DAPT use in LOF allele carriers (P=0.001) varied over time. Risk for major adverse cardiovascular or cerebrovascular was significantly higher in LOF carriers prescribed clopidogrel versus alternative DAPT (adjusted hazard ratio, 4.65; 95% confidence interval, 2.22-10.0; P<0.001), whereas no significant difference was observed in those without a LOF allele (adjusted hazard ratio, 1.37; 95% confidence interval, 0.72-2.85; P=0.347). Bleeding event rates were similar across groups (log-rank P=0.816). CONCLUSIONS Implementing CYP2C19 genotype-guided DAPT is feasible and sustainable in a real-world setting but challenging to maintain at a consistently high level of fidelity. The higher risk of major adverse cardiovascular or cerebrovascular associated with clopidogrel use in CYP2C19 LOF allele carriers suggests that use of genotype-guided DAPT in practice may improve clinical outcomes.
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Affiliation(s)
- Craig R Lee
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill.
| | - Vindhya B Sriramoju
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - Alexandra Cervantes
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - Lucius A Howell
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - Nicholas Varunok
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - Shivanshu Madan
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - Kasey Hamrick
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - Melissa J Polasek
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - John Andrew Lee
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - Megan Clarke
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - Jonathan D Cicci
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - Karen E Weck
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
| | - George A Stouffer
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy (C.R.L., A.C., K.H., M.J.P., J.A.L.), UNC Center for Pharmacogenomics and Individualized Therapy (C.R.L., K.E.W.), UNC McAllister Heart Institute (C.R.L., G.A.S.), Division of Cardiology, UNC School of Medicine (V.B.S., L.A.H., N.V., S.M., G.A.S.), Department of Pharmacy, UNC HealthCare Medical Center (M.C., J.D.C.), and Department of Pathology and Laboratory Medicine, UNC School of Medicine (K.E.W.), University of North Carolina at Chapel Hill
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20
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Horowitz CR, Orlando LA, Slavotinek AM, Peterson J, Angelo F, Biesecker B, Bonham VL, Cameron LD, Fullerton SM, Gelb BD, Goddard KAB, Hailu B, Hart R, Hindorff LA, Jarvik GP, Kaufman D, Kenny EE, Knight SJ, Koenig BA, Korf BR, Madden E, McGuire AL, Ou J, Wasserstein MP, Robinson M, Leventhal H, Sanderson SC. The Genomic Medicine Integrative Research Framework: A Conceptual Framework for Conducting Genomic Medicine Research. Am J Hum Genet 2019; 104:1088-1096. [PMID: 31104772 PMCID: PMC6556906 DOI: 10.1016/j.ajhg.2019.04.006] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Accepted: 04/10/2019] [Indexed: 01/13/2023] Open
Abstract
Conceptual frameworks are useful in research because they can highlight priority research domains, inform decisions about interventions, identify outcomes and factors to measure, and display how factors might relate to each other to generate and test hypotheses. Discovery, translational, and implementation research are all critical to the overall mission of genomic medicine and prevention, but they have yet to be organized into a unified conceptual framework. To fill this gap, our diverse team collaborated to develop the Genomic Medicine Integrative Research (GMIR) Framework, a simple but comprehensive tool to aid the genomics community in developing research questions, strategies, and measures and in integrating genomic medicine and prevention into clinical practice. Here we present the GMIR Framework and its development, along with examples of its use for research development, demonstrating how we applied it to select and harmonize measures for use across diverse genomic medicine implementation projects. Researchers can utilize the GMIR Framework for their own research, collaborative investigations, and clinical implementation efforts; clinicians can use it to establish and evaluate programs; and all stakeholders can use it to help allocate resources and make sure that the full complexity of etiology is included in research and program design, development, and evaluation.
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Affiliation(s)
- Carol R Horowitz
- Center for Health Equity and Community Engaged Research, Icahn School of Medicine, New York, NY 10029, USA; Department of Population Health Science and Policy, Icahn School of Medicine, New York, NY 10029, USA.
| | - Lori A Orlando
- Duke Center for Applied Genomics and Precision Medicine, Durham, NC 27708, USA
| | - Anne M Slavotinek
- Department of Pediatrics, Division of Genetics, University of California, San Francisco, CA 94143, USA
| | - Josh Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Frank Angelo
- Clinical Sequencing Evidence-Generating Research Coordinating Center, University of Washington, Seattle, WA 98195, USA; Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
| | | | - Vence L Bonham
- Social and Behavioral Research Branch, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | | | - Stephanie M Fullerton
- Clinical Sequencing Evidence-Generating Research Coordinating Center, University of Washington, Seattle, WA 98195, USA; Department of Bioethics and Humanities, University of Washington, Seattle, WA 98195, USA
| | - Bruce D Gelb
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Benyam Hailu
- Division of Scientific Programs, National Institute of Minority Health and Health Disparities, NIH, Bethesda, MD 20892, USA
| | - Ragan Hart
- Clinical Sequencing Evidence-Generating Research Coordinating Center, University of Washington, Seattle, WA 98195, USA; Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
| | - Lucia A Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Gail P Jarvik
- Clinical Sequencing Evidence-Generating Research Coordinating Center, University of Washington, Seattle, WA 98195, USA; Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
| | - Dave Kaufman
- Division of Genomics and Society, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Eimear E Kenny
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Center for Population Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sara J Knight
- Division of Preventive Medicine, University of Alabama at Birmingham and Birmingham VA Medical Center, Birmingham, AL 35205, USA
| | - Barbara A Koenig
- Program in Bioethics, University of California, San Francisco, CA 94143, USA
| | - Bruce R Korf
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL 35205, USA
| | - Ebony Madden
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Amy L McGuire
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jeffrey Ou
- Clinical Sequencing Evidence-Generating Research Coordinating Center, University of Washington, Seattle, WA 98195, USA; Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
| | - Melissa P Wasserstein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Children's Hospital at Montefiore, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | | | - Howard Leventhal
- Department of Psychology, Institute for Health, Rutgers University, New Brunswick, NJ 08901, USA
| | - Saskia C Sanderson
- Behavioural Science and Health Department, University College London, London, UK
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Zhang XG, Zhu XQ, Xue J, Li ZZ, Jiang HY, Hu L, Yue YH. Personalised antiplatelet therapy based on pharmacogenomics in acute ischaemic minor stroke and transient ischaemic attack: study protocol for a randomised controlled trial. BMJ Open 2019; 9:e028595. [PMID: 31123001 PMCID: PMC6538075 DOI: 10.1136/bmjopen-2018-028595] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 04/06/2019] [Accepted: 04/08/2019] [Indexed: 01/16/2023] Open
Abstract
INTRODUCTION Antiplatelet therapy combining aspirin and clopidogrel is considered to be a key intervention for acute ischaemic minor stroke (AIMS) and transient ischaemic attack (TIA). However, the interindividual variability in response to clopidogrel resulting from the polymorphisms in clopidogrel metabolism-related genes has greatly limited its efficacy. To date, there are no reports on individualised antiplatelet therapy for AIMS and TIA based on the genetic testing and clinical features. Therefore, we conduct this randomised controlled trial to validate the hypothesis that the individualised antiplatelet therapy selected on the basis of a combination of genetic information and clinical features would lead to better clinical outcomes compared with the standard care based only on clinical features in patients with AIMS or TIA. METHODS AND ANALYSIS This trial will recruit 2382 patients with AIMS or TIA who meet eligibility criteria. Patients are randomly assigned in a 1:1 ratio to pharmacogenetic group and standard group. Both groups receive a loading dose of 300 mg aspirin and 300 mg clopidogrel on day 1, followed by 100 mg aspirin per day on days 2-365. The P2Y12 receptor antagonist is selected by the clinician according to the genetic information and clinical features for pharmacogenetic group and clinical features for the standard group on days 2-21. The primary efficacy endpoint is a new stroke event (ischaemic or haemorrhagic) that happens within 1 year. The secondary efficacy endpoint is analysed as the individual or composite outcomes of the new clinical vascular event (ischaemic stroke, haemorrhagic stroke, myocardial infarction or vascular death). Baseline characteristics and outcomes after treatment will be evaluated. ETHICS AND DISSEMINATION This protocol has been approved by the ethics committee of Yangpu Hospital, Tongji University School of Medicine (No. LL-2018-KY-012). We will submit the results of this trial for publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER ChiCTR1800019911; Pre-results.
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Affiliation(s)
- Xiao-Guang Zhang
- Department of Neurology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Xiao-Qiong Zhu
- Department of Neurology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jie Xue
- Department of Neurology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Zhi-Zhang Li
- Department of Neurology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Hua-Yu Jiang
- Department of Neurology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Liang Hu
- Department of Neurology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Yun-Hua Yue
- Department of Neurology, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
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22
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Orlando LA, Voils C, Horowitz CR, Myers RA, Arwood MJ, Cicali EJ, McDonough CW, Pollin TI, Guan Y, Levy KD, Ramirez A, Quittner A, Madden EB. IGNITE network: Response of patients to genomic medicine interventions. Mol Genet Genomic Med 2019; 7:e636. [PMID: 30895746 PMCID: PMC6503007 DOI: 10.1002/mgg3.636] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 01/26/2019] [Accepted: 02/11/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The IGNITE network funds six genomic medicine projects. Though interventions varied, we hypothesized that synergies across projects could be leveraged to better understand the participant experiences with genomic medicine interventions. Therefore, we performed cross-network analyses to identify associations between participant demographics and attitudes toward the intervention (attitude), plan to share results (share), and quality of life (QOL). METHODS Data collection for demographics, attitude, share, and QOL surveys were standardized across projects. Recruitment and survey administration varied by each project's protocol. RESULTS Participants (N = 6,817) were 67.2% (N = 4,584) female, and 37.4% (N = 3,544) were minority. Mean age = 54.0 (sd 14.a). Younger participants were as follows: (1) more positive in attitude pre-intervention (1.15-fold decrease/10-year age increase (OR)) and more negative after (1.14-fold increase OR); (2) higher in QOL pre-intervention (1.07-fold increase OR) and postintervention; (3) more likely to share results (1.12-fold increase OR). Race was significant when sharing results (white participants increased OR = 1.88), but not for change in QOL pre-postintervention or attitude. CONCLUSION Our findings demonstrate the feasibility of this approach and identified a few key themes which are as follows: age was consistently significant across the three outcomes, whereas race had less of an impact than expected. However, these are only associations and thus warrant further study.
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Affiliation(s)
- Lori A Orlando
- Department of Medicine and the Center for Applied Genomics and Precision Medicine, Duke University, Durham, North Carolina
| | - Corrine Voils
- School of Medicine & Public Health, William S Middleton Memorial Veterans Hospital, University of Wisconsin, Madison, Wisconsin
| | - Carol R Horowitz
- Department of Population Health Sciences and Policy and the Center for Health Equity and Community Engaged Research, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Rachel A Myers
- Department of Medicine and the Center for Applied Genomics and Precision Medicine, Duke University, Durham, North Carolina
| | - Meghan J Arwood
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, Florida
| | - Emily J Cicali
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, Florida
| | - Caitrin W McDonough
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, Florida
| | - Toni I Pollin
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Yue Guan
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Kenneth D Levy
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Andrea Ramirez
- Department of Medicine, Vanderbilt University, Nashville, Tennessee
| | - Alexandra Quittner
- Nicklaus Children's Research Institute, Nicklaus Children's Hospital, Miami, Florida
| | - Ebony B Madden
- National Human Genome Research Institute, Bethesda, Maryland
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24
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Schwartz JB, Schmader KE, Hanlon JT, Abernethy DR, Gray S, Dunbar-Jacob J, Holmes HM, Murray MD, Roberts R, Joyner M, Peterson J, Lindeman D, Tai-Seale M, Downey L, Rich MW. Pharmacotherapy in Older Adults with Cardiovascular Disease: Report from an American College of Cardiology, American Geriatrics Society, and National Institute on Aging Workshop. J Am Geriatr Soc 2018; 67:371-380. [PMID: 30536694 DOI: 10.1111/jgs.15634] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
OBJECTIVES To identify the top priority areas for research to optimize pharmacotherapy in older adults with cardiovascular disease (CVD). DESIGN Consensus meeting. SETTING Multidisciplinary workshop supported by the National Institute on Aging, the American College of Cardiology, and the American Geriatrics Society, February 6-7, 2017. PARTICIPANTS Leaders in the Cardiology and Geriatrics communities, (officers in professional societies, journal editors, clinical trialists, Division chiefs), representatives from the NIA; National Heart, Lung, and Blood Institute; Food and Drug Administration; Centers for Medicare and Medicaid Services, Alliance for Academic Internal Medicine, Patient-Centered Outcomes Research Institute, Agency for Healthcare Research and Quality, pharmaceutical industry, and trainees and early career faculty with interests in geriatric cardiology. MEASUREMENTS Summary of workshop proceedings and recommendations. RESULTS To better align older adults' healthcare preferences with their care, research is needed to improve skills in patient engagement and communication. Similarly, to coordinate and meet the needs of older adults with multiple comorbidities encountering multiple healthcare providers and systems, systems and disciplines must be integrated. The lack of data from efficacy trials of CVD medications relevant to the majority of older adults creates uncertainty in determining the risks and benefits of many CVD therapies; thus, developing evidence-based guidelines for older adults with CVD is a top research priority. Polypharmacy and medication nonadherence lead to poor outcomes in older people, making research on appropriate prescribing and deprescribing to reduce polypharmacy and methods to improve adherence to beneficial therapies a priority. CONCLUSION The needs and circumstances of older adults with CVD differ from those that the current medical system has been designed to meet. Optimizing pharmacotherapy in older adults will require new data from traditional and pragmatic research to determine optimal CVD therapy, reduce polypharmacy, increase adherence, and meet person-centered goals. Better integration of the multiple systems and disciplines involved in the care of older adults will be essential to implement and disseminate best practices. J Am Geriatr Soc 67:371-380, 2019.
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Affiliation(s)
- Janice B Schwartz
- Divisions of Geriatrics and Clinical Pharmacology, Departments of Medicine and Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California
| | - Kenneth E Schmader
- Division of Geriatrics, Department of Medicine, Duke University Medical Center, Durham, North Carolina.,Geriatric Research, Education, and Clinical Center, Durham Veterans Affairs Medical Center, Durham, North Carolina
| | - Joseph T Hanlon
- Division of Geriatrics, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Darrell R Abernethy
- Office of Clinical Pharmacology, U.S. Food & Drug Administration, Silver Spings, Maryland
| | - Shelly Gray
- Department of Pharmacy, University of Washington, Seattle, Washington
| | | | - Holly M Holmes
- Geriatric and Palliative Medicine, Department of Medicine, McGovern Medical School, Houston, Texas
| | - Michael D Murray
- Department of Pharmacy Practice, Regenstrief Institute, Purdue University, West Lafayette, Indiana
| | - Robert Roberts
- Department of Medicine, College of Medicine, University of Arizona, Phoenix, Arizona
| | - Michael Joyner
- Departments of Anesthesiology and Perioperative Medicine and Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota
| | - Josh Peterson
- Departments of Biomedical Informatics and Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - David Lindeman
- CITRIS and the Banatao Institute, University of California, Berkeley, California
| | - Ming Tai-Seale
- Division of Health Policy, Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California
| | - Laura Downey
- Concordance Health Solutions, West Lafayette, Indiana.,Krannert School of Management, Purdue University, West Lafayette, Indiana
| | - Michael W Rich
- Cardiovascular Division, Department of Internal Medicine, Washington University, St. Louis, Missouri
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Cavallari LH, Obeng AO. Genetic Determinants of P2Y 12 Inhibitors and Clinical Implications. Interv Cardiol Clin 2018; 6:141-149. [PMID: 27886818 DOI: 10.1016/j.iccl.2016.08.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
There is significant interpatient variability in clopidogrel effectiveness, which is due in part to cytochrome P450 (CYP) 2C19 genotype. Approximately 30% of individuals carry CYP2C19 loss-of-function alleles, which have been consistently shown to reduce clopidogrel effectiveness after an acute coronary syndrome and percutaneous coronary intervention. Guidelines recommend consideration of prasugrel or ticagrelor in these patients. A clinical trial examining outcomes with CYP2C19 genotype-guided antiplatelet therapy is ongoing. In the meantime, based on the evidence available to date, several institutions have started clinically implementing CYP2C19 genotyping to assist with antiplatelet selection after percutaneous coronary intervention.
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Affiliation(s)
- Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics, University of Florida, 1333 Center Drive, PO Box 100486, Gainesville, FL 32610, USA.
| | - Aniwaa Owusu Obeng
- Division of General Internal Medicine, Department of Medicine, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, USA; Department of Pharmacy, The Mount Sinai Hospital, New York, NY, USA
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Empey PE, Stevenson JM, Tuteja S, Weitzel KW, Angiolillo DJ, Beitelshees AL, Coons JC, Duarte JD, Franchi F, Jeng LJ, Johnson JA, Kreutz RP, Limdi NA, Maloney KA, Obeng AO, Peterson JF, Petry N, Pratt VM, Rollini F, Scott SA, Skaar TC, Vesely MR, Stouffer GA, Wilke RA, Cavallari LH, Lee CR. Multisite Investigation of Strategies for the Implementation of CYP2C19 Genotype-Guided Antiplatelet Therapy. Clin Pharmacol Ther 2018; 104:664-674. [PMID: 29280137 PMCID: PMC6019555 DOI: 10.1002/cpt.1006] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Revised: 11/27/2017] [Accepted: 12/20/2017] [Indexed: 01/05/2023]
Abstract
CYP2C19 genotype-guided antiplatelet therapy following percutaneous coronary intervention is increasingly implemented in clinical practice. However, challenges such as selecting a testing platform, communicating test results, building clinical decision support processes, providing patient and provider education, and integrating methods to support the translation of emerging evidence to clinical practice are barriers to broad adoption. In this report, we compare and contrast implementation strategies of 12 early adopters, describing solutions to common problems and initial performance metrics for each program. Key differences between programs included the test result turnaround time and timing of therapy changes, which are both related to the CYP2C19 testing model and platform used. Sites reported the need for new informatics infrastructure, expert clinicians such as pharmacists to interpret results, physician champions, and ongoing education. Consensus lessons learned are presented to provide a path forward for those seeking to implement similar clinical pharmacogenomics programs within their institutions.
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Affiliation(s)
- Philip E. Empey
- Department of Pharmacy and Therapeutics, Center for Clinical Pharmaceutical Sciences, University of Pittsburgh School of Pharmacy, Pittsburgh, PA
| | - James M. Stevenson
- Department of Pharmacy and Therapeutics, Center for Clinical Pharmaceutical Sciences, University of Pittsburgh School of Pharmacy, Pittsburgh, PA
| | - Sony Tuteja
- Department of Medicine, Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Kristin W. Weitzel
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL
| | - Dominick J. Angiolillo
- Department of Medicine, Division of Cardiology, University of Florida College of Medicine, Jacksonville, FL
| | - Amber L. Beitelshees
- Department of Medicine and Program for Personalized and Genomic Medicine, University of Maryland, Baltimore, MD
| | - James C. Coons
- Department of Pharmacy and Therapeutics, Center for Clinical Pharmaceutical Sciences, University of Pittsburgh School of Pharmacy, Pittsburgh, PA
| | - Julio D. Duarte
- Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, IL
| | - Francesco Franchi
- Department of Medicine, Division of Cardiology, University of Florida College of Medicine, Jacksonville, FL
| | - Linda J.B. Jeng
- Department of Medicine and Program for Personalized and Genomic Medicine, University of Maryland, Baltimore, MD
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL
| | - Rolf P Kreutz
- Department of Medicine, Krannert Institute of Cardiology, Indiana University School of Medicine, Indianapolis, IN
| | - Nita A. Limdi
- Department of Neurology, University of Alabama at Birmingham, Birmingham AL
| | - Kristin A. Maloney
- Department of Medicine and Program for Personalized and Genomic Medicine, University of Maryland, Baltimore, MD
| | - Aniwaa Owusu Obeng
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai; and Pharmacy Department, The Mount Sinai Hospital, New York, NY
| | - Josh F. Peterson
- Departments of Biomedical Informatics and Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Natasha Petry
- Department of Pharmacy Practice, North Dakota State University, Fargo, ND
| | - Victoria M. Pratt
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Fabiana Rollini
- Department of Medicine, Division of Cardiology, University of Florida College of Medicine, Jacksonville, FL
| | - Stuart A. Scott
- Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY and Sema4, a Mount Sinai venture, Stamford, CT
| | - Todd C. Skaar
- Department of Medicine, Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN
| | - Mark R. Vesely
- Department of Medicine and Program for Personalized and Genomic Medicine, University of Maryland, Baltimore, MD
| | - George A. Stouffer
- Division of Cardiology, School of Medicine and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Russell A. Wilke
- Department of Internal Medicine, University of South Dakota Sanford School of Medicine, Sioux Falls, SD
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL
| | - Craig R. Lee
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC
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Mukerjee G, Huston A, Kabakchiev B, Piquette-Miller M, van Schaik R, Dorfman R. User considerations in assessing pharmacogenomic tests and their clinical support tools. NPJ Genom Med 2018; 3:26. [PMID: 30210808 PMCID: PMC6133969 DOI: 10.1038/s41525-018-0065-4] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 08/10/2018] [Accepted: 08/13/2018] [Indexed: 12/18/2022] Open
Abstract
Pharmacogenomic (PGx) testing is gaining recognition from physicians, pharmacists and patients as a tool for evidence-based medication management. However, seemingly similar PGx testing panels (and PGx-based decision support tools) can diverge in their technological specifications, as well as the genetic factors that determine test specificity and sensitivity, and hence offer different values for users. Reluctance to embrace PGx testing is often the result of unfamiliarity with PGx technology, a lack of knowledge about the availability of curated guidelines/evidence for drug dosing recommendations, and an absence of wide-spread institutional implementation efforts and educational support. Demystifying an often confusing and variable PGx marketplace can lead to greater acceptance of PGx as a standard-of-care practice that improves drug outcomes and provides a lifetime value for patients. Here, we highlight the key underlying factors of a PGx test that should be considered, and discuss the current progress of PGx implementation.
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Affiliation(s)
| | - Andrea Huston
- GeneYouIn Inc., 156 Front St. W., Toronto, ON Canada
| | - Boyko Kabakchiev
- GeneYouIn Inc., 156 Front St. W., Toronto, ON Canada.,2Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON Canada
| | | | - Ron van Schaik
- 4International Expert Center Pharmacogenetics, Department of Clinical Chemistry, Erasmus University Medical Center, Rotterdam, The Netherlands
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Klein MD, Lee CR, Stouffer GA. Clinical outcomes of CYP2C19 genotype-guided antiplatelet therapy: existing evidence and future directions. Pharmacogenomics 2018; 19:1039-1046. [DOI: 10.2217/pgs-2018-0072] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
It is well established that the CYP2C19 nonfunctional *2 and *3 polymorphisms impair the bioactivation and antiplatelet effects of clopidogrel, and increase the risk of adverse cardiovascular events following percutaneous coronary intervention. In contrast, CYP2C19 genotype does not impact clinical response to prasugrel or ticagrelor. Recent studies have evaluated the impact of CYP2C19 genotype-guided selection of antiplatelet therapy on clinical outcomes and begun to close some of the gaps in knowledge and uncertainty that have impeded widespread clinical implementation of this precision medicine approach. This review will critically evaluate recent data and offer new insight into the potential clinical utility of genotype-guided antiplatelet therapy in the context of current clinical practice guidelines.
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Affiliation(s)
- Melissa D Klein
- Division of Cardiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Craig R Lee
- McAllister Heart Institute, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Division of Pharmacotherapy & Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Center for Pharmacogenomics & Individualized Therapy, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - George A Stouffer
- Division of Cardiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- McAllister Heart Institute, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Abstract
Considerable interindividual variability in response to cardiovascular pharmacotherapy exists with drug responses varying from being efficacious to inadequate to induce severe adverse events. Fueled by advancements and multidisciplinary collaboration across disciplines such as genetics, bioinformatics, and basic research, the vision of personalized medicine, rather than a one-size-fits-all approach, may be within reach. Pharmacogenetics offers the potential to optimize the benefit-risk profile of drugs by tailoring diagnostic and treatment strategies according to the individual patient. To date, a multitude of studies has tried to delineate the effects of gene-drug interactions for drugs commonly used to treat cardiovascular-related disease. The focus of this review is on how genetic variability may modify drug responsiveness and patient outcomes following therapy with commonly used cardiovascular drugs including clopidogrel, warfarin, statins, and β-blockers. Also included are examples of how genetic studies can be used to guide drug discovery and examples of how genetic information may be deployed in clinical decision making.
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Affiliation(s)
- Peter E Weeke
- Department of Cardiology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark.
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Evans B, Ossorio P. The Challenge of Regulating Clinical Decision Support Software After 21 st Century Cures. AMERICAN JOURNAL OF LAW & MEDICINE 2018; 44:237-251. [PMID: 30106648 DOI: 10.1177/0098858818789418] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Affiliation(s)
- Barbara Evans
- Barbara Evans is a professor at the University of Houston Law Center and Department of Electrical and Computer Engineering. The authors would like to thank Ellen Wright Clayton, Jim Hawkins, Gail Javitt, and Susan M. Wolf for helpful comments. Disclosures: This work received funding from the NIH/NHGRI LawSeqSM project, NHGRI/NCI 1R01HG008605 and from the University of Houston Law Foundation
| | - Pilar Ossorio
- Pilar Ossorio is a professor at the University of Wisconsin Law School and Morgridge Institute for Research
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Roden DM, Van Driest SL, Mosley JD, Wells QS, Robinson JR, Denny JC, Peterson JF. Benefit of Preemptive Pharmacogenetic Information on Clinical Outcome. Clin Pharmacol Ther 2018; 103:787-794. [PMID: 29377064 PMCID: PMC6134843 DOI: 10.1002/cpt.1035] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 01/08/2018] [Accepted: 01/22/2018] [Indexed: 12/13/2022]
Abstract
The development of new knowledge around the genetic determinants of variable drug action has naturally raised the question of how this new knowledge can be used to improve the outcome of drug therapy. Two broad approaches have been taken: a point-of-care approach in which genotyping for specific variant(s) is undertaken at the time of drug prescription, and a preemptive approach in which multiple genetic variants are typed in an individual patient and the information archived for later use when a drug with a "pharmacogenetic story" is prescribed. This review addresses the current state of implementation, the rationale for these approaches, and barriers that must be overcome. Benefits to pharmacogenetic testing are only now being defined and will be discussed.
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Affiliation(s)
- Dan M. Roden
- Department of Medicine, Vanderbilt University Medical Center Nashville, TN
- Department of Pharmacology, Vanderbilt University Medical Center Nashville, TN
- Department of Biomedical Informatics, Vanderbilt University Medical Center Nashville, TN
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center Nashville, TN
- Department of Pediatrics, Vanderbilt University Medical Center Nashville, TN
| | - Jonathan D. Mosley
- Department of Medicine, Vanderbilt University Medical Center Nashville, TN
- Department of Biomedical Informatics, Vanderbilt University Medical Center Nashville, TN
| | - Quinn S. Wells
- Department of Medicine, Vanderbilt University Medical Center Nashville, TN
| | - Jamie R. Robinson
- Department of Biomedical Informatics, Vanderbilt University Medical Center Nashville, TN
- Department of Surgery, Vanderbilt University Medical Center Nashville, TN
| | - Joshua C. Denny
- Department of Medicine, Vanderbilt University Medical Center Nashville, TN
- Department of Biomedical Informatics, Vanderbilt University Medical Center Nashville, TN
| | - Josh F. Peterson
- Department of Medicine, Vanderbilt University Medical Center Nashville, TN
- Department of Biomedical Informatics, Vanderbilt University Medical Center Nashville, TN
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Overby CL, Thompkins P, Lehmann H, Chute CG, Sheffield JS. Value of Genetics-informed Drug Dosing Guidance in Pregnant Women: A Needs Assessment with Obstetric Healthcare Providers at Johns Hopkins. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2018; 2017:1342-1351. [PMID: 29854203 PMCID: PMC5977707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
In order to better understand the potential value of genetics-informed drug dose guidance to obstetric healthcare providers at Johns Hopkins we administered a web-based needs assessment survey. The survey included questions about: 1) experience with adjusting drug doses during pregnancy; 2) comfort prescribing medications to pregnant women with chronic conditions; 3) awareness and use of genetics-informed dosing guidance; and 4) perceived value of access to services to provide genetics-informed dosing guidance. Among thirty-one respondents, 81% indicated an interest in access to genetics-informed drug dose guidance, particularly a mobile or electronic health record (EHR) application. It was indicated, however, that genetics is one of many characteristics that influence dose adjustments during pregnancy. This study motivates future research to help obstetric healthcare providers tailor drug dose to individual patients based upon models integrating multiple patient characteristics, including genetics.
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Affiliation(s)
- Casey L Overby
- Division of General Internal Medicine
- Institute for Clinical & Translational Research
- Division of Health Sciences Informatics
| | | | | | - Christopher G Chute
- Division of General Internal Medicine
- Institute for Clinical & Translational Research
- Division of Health Sciences Informatics
| | - Jeanne S Sheffield
- Division of Maternal & Fetal Medicine; Johns Hopkins University School of Medicine, Baltimore, MD, USA
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33
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Volpi S, Bult CJ, Chisholm RL, Deverka PA, Ginsburg GS, Jacob HJ, Kasapi M, McLeod HL, Roden DM, Williams MS, Green ED, Rodriguez LL, Aronson S, Cavallari LH, Denny JC, Dressler LG, Johnson JA, Klein TE, Leeder JS, Piquette-Miller M, Perera M, Rasmussen-Torvik LJ, Rehm HL, Ritchie MD, Skaar TC, Wagle N, Weinshilboum R, Weitzel KW, Wildin R, Wilson J, Manolio TA, Relling MV. Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects. Clin Pharmacol Ther 2018; 103:778-786. [PMID: 29460415 DOI: 10.1002/cpt.1048] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 01/31/2018] [Accepted: 02/14/2018] [Indexed: 12/29/2022]
Abstract
Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them.
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Affiliation(s)
- Simona Volpi
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Carol J Bult
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine, USA
| | - Rex L Chisholm
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | | | - Geoffrey S Ginsburg
- Duke Center for Applied Genomic and Precision Medicine, Duke University, Durham, North Carolina, USA
| | - Howard J Jacob
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Melpomeni Kasapi
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Howard L McLeod
- DeBartolo Family Personalized Medicine Institute, Moffitt Cancer Center, Tampa, Florida, USA
| | - Dan M Roden
- Department of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Marc S Williams
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, USA
| | - Eric D Green
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Laura Lyman Rodriguez
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, Florida, USA
| | - Joshua C Denny
- Departments of Biomedical Informatics and Medicine, Vanderbilt University, Nashville, Tennessee, USA
| | - Lynn G Dressler
- Mission Health, Personalized Medicine Program, Asheville, North Carolina, USA
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, Florida, USA
| | - Teri E Klein
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - J Steven Leeder
- Division of Clinical Pharmacology, Toxicology and Therapeutic Innovation, Children's Mercy Hospital, Kansas City, Missouri, USA
| | | | - Minoli Perera
- Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Heidi L Rehm
- Department of Pathology, Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Todd C Skaar
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Nikhil Wagle
- Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Richard Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics and Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Kristin W Weitzel
- Department of Pharmacotherapy & Translational Research, University of Florida College of Pharmacy, Gainesville, Florida, USA
| | - Robert Wildin
- Departments of Pathology and Laboratory Medicine, and Pediatrics, University of Vermont Medical Center, Burlington, Vermont, USA
| | | | - Teri A Manolio
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Mary V Relling
- Pharmaceutical Sciences Department, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
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Notarangelo FM, Maglietta G, Bevilacqua P, Cereda M, Merlini PA, Villani GQ, Moruzzi P, Patrizi G, Malagoli Tagliazucchi G, Crocamo A, Guidorossi A, Pigazzani F, Nicosia E, Paoli G, Bianchessi M, Comelli MA, Caminiti C, Ardissino D. Pharmacogenomic Approach to Selecting Antiplatelet Therapy in Patients With Acute Coronary Syndromes: The PHARMCLO Trial. J Am Coll Cardiol 2018. [PMID: 29540324 DOI: 10.1016/j.jacc.2018.02.029] [Citation(s) in RCA: 136] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
BACKGROUND Although clopidogrel is still frequently used in patients with acute coronary syndromes (ACS), its efficacy is hampered by interpatient response variability caused by genetic polymorphisms associated with clopidogrel's metabolism. OBJECTIVES The goal of this study was to evaluate whether selecting antiplatelet therapy (clopidogrel, prasugrel, or ticagrelor) on the basis of a patient's genetic and clinical characteristics leads to better clinical outcomes compared with the standard of care, which bases the selection on clinical characteristics alone. METHODS Patients hospitalized for ACS were randomly assigned to standard of care or the pharmacogenomic arm, which included the genotyping of ABCB1, CYP2C19*2, and CYP2C19*17 using an ST Q3 system that provides data within 70 min at each patient's bedside. The patients were followed up for 12 ± 1 month for the primary composite endpoint of cardiovascular death and the first occurrence of nonfatal myocardial infarction, nonfatal stroke, and major bleeding defined according to Bleeding Academic Research Consortium type 3 to 5 criteria. RESULTS After enrolling 888 patients, the study was prematurely stopped. Clopidogrel was used more frequently in the standard-of-care arm (50.7% vs. 43.3%), ticagrelor in the pharmacogenomic arm (42.6% vs. 32.7%; p = 0.02), and prasugrel was equally used in both arms. The primary endpoint occurred in 71 patients (15.9%) in the pharmacogenomic arm and in 114 (25.9%) in the standard-of-care arm (hazard ratio: 0.58; 95% confidence interval: 0.43 to 0.78; p < 0.001). CONCLUSIONS A personalized approach to selecting antiplatelet therapy for patients with ACS may reduce ischemic and bleeding events. (Pharmacogenetics of Clopidogrel in Patients With Acute Coronary Syndromes [PHARMCLO]; NCT03347435).
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Affiliation(s)
| | - Giuseppe Maglietta
- Division of Research and Innovation, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy; Department of Statistics, Computer Science, Applications, Università di Firenze, Florence, Italy
| | - Paola Bevilacqua
- Division of Cardiology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Marco Cereda
- ST Microelectronics S.R.L., Agrate Brianza, Monza Brianza, Italy
| | | | | | - Paolo Moruzzi
- Division of Cardiology, Azienda Territoriale di Parma, Fidenza, Italy
| | - Giampiero Patrizi
- Division of Cardiology, Azienda Territoriale di Modena, Carpi, Italy
| | - Guidantonio Malagoli Tagliazucchi
- Division of Cardiology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy; Division of Research and Innovation, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Antonio Crocamo
- Division of Cardiology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Angela Guidorossi
- Division of Cardiology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Filippo Pigazzani
- Division of Cardiology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Elisa Nicosia
- Division of Cardiology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Giorgia Paoli
- Division of Cardiology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Marco Bianchessi
- ST Microelectronics S.R.L., Agrate Brianza, Monza Brianza, Italy
| | | | - Caterina Caminiti
- Division of Research and Innovation, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Diego Ardissino
- Division of Cardiology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy.
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35
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Denny JC, Van Driest SL, Wei WQ, Roden DM. The Influence of Big (Clinical) Data and Genomics on Precision Medicine and Drug Development. Clin Pharmacol Ther 2018; 103:409-418. [PMID: 29171014 PMCID: PMC5805632 DOI: 10.1002/cpt.951] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Revised: 11/15/2017] [Accepted: 11/19/2017] [Indexed: 12/30/2022]
Abstract
Drug development continues to be costly and slow, with medications failing due to lack of efficacy or presence of toxicity. The promise of pharmacogenomic discovery includes tailoring therapeutics based on an individual's genetic makeup, rational drug development, and repurposing medications. Rapid growth of large research cohorts, linked to electronic health record (EHR) data, fuels discovery of new genetic variants predicting drug action, supports Mendelian randomization experiments to show drug efficacy, and suggests new indications for existing medications. New biomedical informatics and machine-learning approaches advance the ability to interpret clinical information, enabling identification of complex phenotypes and subpopulations of patients. We review the recent history of use of "big data" from EHR-based cohorts and biobanks supporting these activities. Future studies using EHR data, other information sources, and new methods will promote a foundation for discovery to more rapidly advance precision medicine.
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Affiliation(s)
- Joshua C. Denny
- Department of Biomedical Informatics, Vanderbilt University Medical Center
- Department of Medicine, Vanderbilt University Medical Center
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center
- Department of Pediatrics, Vanderbilt University Medical Center
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center
| | - Dan M. Roden
- Department of Biomedical Informatics, Vanderbilt University Medical Center
- Department of Medicine, Vanderbilt University Medical Center
- Department of Pharmacology, Vanderbilt University Medical Center
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Abstract
No therapies have been shown to improve outcomes in patients with acute kidney injury (AKI). Given the high morbidity and mortality associated with AKI this represents an important unmet medical need. A common feature of all of the therapeutic development efforts for AKI is that none were driven by target selection or preclinical modeling that was based primarily on human data. This is important when considering a heterogeneous and dynamic condition such as AKI, in which in the absence of more accurate molecular classifications, clinical cohorts are likely to include patients with different types of injury at different stages in the injury and repair continuum. The National Institutes of Health precision medicine initiative offers an opportunity to address this. By creating a molecular tissue atlas of AKI, defining patient subgroups, and identifying critical cells and pathways involved in human AKI, this initiative has the potential to transform our current approach to therapeutic discovery. In this review, we discuss the opportunities and challenges that this initiative presents, with a specific focus on AKI, what additional efforts will be needed to apply these discoveries to therapeutic development, and how we believe this effort might lead to the development of new therapeutics for subsets of patients with AKI.
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Affiliation(s)
- Mark de Caestecker
- Nephrology Division, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
| | - Raymond Harris
- Nephrology Division, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
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37
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Haga SB. Integrating pharmacogenetic testing into primary care. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2017; 2:327-336. [PMID: 31853504 DOI: 10.1080/23808993.2017.1398046] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction Pharmacogenetic (PGx) testing has greatly expanded due to enhanced understanding of the role of genes in drug response and advances in DNA-based testing technology development. As many primary care visits result in a prescription, the use of PGx testing may be particularly beneficial in this setting. However, integration of PGx testing may be limited as no uniform approach to delivery of tests has been established and providers are ill-prepared to integrate PGx testing into routine care. Areas covered In this paper, the readiness of primary care practitioners are reviewed as well as strategies to address these barriers based on published research and ongoing activities on education and implementation of PGx testing. Expert Commentary Widespread integration of PGx testing will warrant continued education and point-of-care decisional support. Primary care providers may also benefit from consultation services or team-based care with laboratory medicine specialists, pharmacists, and genetic counselors.
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Affiliation(s)
- Susanne B Haga
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, 304 Research Drive, Durham, NC 27708, USA,
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Cavallari LH, Lee CR, Beitelshees AL, Cooper-DeHoff RM, Duarte JD, Voora D, Kimmel SE, McDonough CW, Gong Y, Dave CV, Pratt VM, Alestock TD, Anderson RD, Alsip J, Ardati AK, Brott BC, Brown L, Chumnumwat S, Clare-Salzler MJ, Coons JC, Denny JC, Dillon C, Elsey AR, Hamadeh IS, Harada S, Hillegass WB, Hines L, Horenstein RB, Howell LA, Jeng LJB, Kelemen MD, Lee YM, Magvanjav O, Montasser M, Nelson DR, Nutescu EA, Nwaba DC, Pakyz RE, Palmer K, Peterson JF, Pollin TI, Quinn AH, Robinson SW, Schub J, Skaar TC, Smith DM, Sriramoju VB, Starostik P, Stys TP, Stevenson JM, Varunok N, Vesely MR, Wake DT, Weck KE, Weitzel KW, Wilke RA, Willig J, Zhao RY, Kreutz RP, Stouffer GA, Empey PE, Limdi NA, Shuldiner AR, Winterstein AG, Johnson JA. Multisite Investigation of Outcomes With Implementation of CYP2C19 Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention. JACC Cardiovasc Interv 2017; 11:181-191. [PMID: 29102571 DOI: 10.1016/j.jcin.2017.07.022] [Citation(s) in RCA: 196] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Revised: 07/07/2017] [Accepted: 07/11/2017] [Indexed: 01/14/2023]
Abstract
OBJECTIVES This multicenter pragmatic investigation assessed outcomes following clinical implementation of CYP2C19 genotype-guided antiplatelet therapy after percutaneous coronary intervention (PCI). BACKGROUND CYP2C19 loss-of-function alleles impair clopidogrel effectiveness after PCI. METHODS After clinical genotyping, each institution recommended alternative antiplatelet therapy (prasugrel, ticagrelor) in PCI patients with a loss-of-function allele. Major adverse cardiovascular events (defined as myocardial infarction, stroke, or death) within 12 months of PCI were compared between patients with a loss-of-function allele prescribed clopidogrel versus alternative therapy. Risk was also compared between patients without a loss-of-function allele and loss-of-function allele carriers prescribed alternative therapy. Cox regression was performed, adjusting for group differences with inverse probability of treatment weights. RESULTS Among 1,815 patients, 572 (31.5%) had a loss-of-function allele. The risk for major adverse cardiovascular events was significantly higher in patients with a loss-of-function allele prescribed clopidogrel versus alternative therapy (23.4 vs. 8.7 per 100 patient-years; adjusted hazard ratio: 2.26; 95% confidence interval: 1.18 to 4.32; p = 0.013). Similar results were observed among 1,210 patients with acute coronary syndromes at the time of PCI (adjusted hazard ratio: 2.87; 95% confidence interval: 1.35 to 6.09; p = 0.013). There was no difference in major adverse cardiovascular events between patients without a loss-of-function allele and loss-of-function allele carriers prescribed alternative therapy (adjusted hazard ratio: 1.14; 95% confidence interval: 0.69 to 1.88; p = 0.60). CONCLUSIONS These data from real-world observations demonstrate a higher risk for cardiovascular events in patients with a CYP2C19 loss-of-function allele if clopidogrel versus alternative therapy is prescribed. A future randomized study of genotype-guided antiplatelet therapy may be of value.
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Affiliation(s)
- Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida.
| | - Craig R Lee
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | | | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida; Department of Medicine, Division of Cardiovascular Medicine, University of Florida, Gainesville, Florida
| | - Julio D Duarte
- Department of Pharmacy Practice, University of Illinois at Chicago College of Pharmacy, Chicago, Illinois
| | - Deepak Voora
- Department of Medicine, Center for Applied Genomics & Precision Medicine, Duke University, Durham, North Carolina
| | - Stephen E Kimmel
- University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
| | - Caitrin W McDonough
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida
| | - Chintan V Dave
- Department of Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida
| | - Victoria M Pratt
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | | | - R David Anderson
- Department of Medicine, Division of Cardiovascular Medicine, University of Florida, Gainesville, Florida
| | - Jorge Alsip
- Division of Cardiovascular Sciences, Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Amer K Ardati
- Department of Medicine, University of Illinois at Chicago College of Medicine, Chicago, Illinois
| | - Brigitta C Brott
- Division of Cardiovascular Sciences, Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Lawrence Brown
- Veterans Administration Medical Center, Baltimore, Maryland
| | - Supatat Chumnumwat
- Department of Pharmacy Practice, University of Illinois at Chicago College of Pharmacy, Chicago, Illinois
| | - Michael J Clare-Salzler
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida
| | - James C Coons
- Department of Pharmacy and Therapeutics, Center for Clinical Pharmaceutical Sciences, University of Pittsburgh School of Pharmacy, Pittsburgh, Pennsylvania
| | - Joshua C Denny
- Departments of Biomedical Informatics and Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Chrisly Dillon
- Department of Neurology, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Amanda R Elsey
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida
| | - Issam S Hamadeh
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida
| | - Shuko Harada
- Department of Pathology and Hugh Kaul Personalized Medicine Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - William B Hillegass
- Heart South Cardiovascular Group, Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| | - Lindsay Hines
- Department of Neuropsychology, University of North Dakota, Fargo, North Dakota
| | | | - Lucius A Howell
- Division of Cardiology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Linda J B Jeng
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Mark D Kelemen
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Yee Ming Lee
- Department of Pharmacy Practice, University of Illinois at Chicago College of Pharmacy, Chicago, Illinois
| | - Oyunbileg Magvanjav
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida
| | - May Montasser
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - David R Nelson
- College of Medicine, Division of Gastroenterology, Hepatology, and Nutrition, University of Florida, Gainesville, Florida
| | - Edith A Nutescu
- Department of Pharmacy Practice, University of Illinois at Chicago College of Pharmacy, Chicago, Illinois; Department of Pharmacy Systems, Outcomes and Policy and Center for Pharmacoepidemiology and Pharmacoeconomic Research, University of Illinois at Chicago College of Pharmacy, Chicago, Illinois
| | - Devon C Nwaba
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Ruth E Pakyz
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Kathleen Palmer
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Josh F Peterson
- Departments of Biomedical Informatics and Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Toni I Pollin
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Alison H Quinn
- Department of Pharmacy Practice, University of Illinois at Chicago College of Pharmacy, Chicago, Illinois
| | - Shawn W Robinson
- Department of Medicine, University of Maryland, Baltimore, Maryland; Veterans Administration Medical Center, Baltimore, Maryland
| | - Jamie Schub
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Todd C Skaar
- Department of Medicine, Krannert Institute of Cardiology & Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana
| | - D Max Smith
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida
| | - Vindhya B Sriramoju
- Division of Cardiology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Petr Starostik
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida
| | - Tomasz P Stys
- Department of Medicine, University of South Dakota, Sanford School of Medicine, Sioux Falls, South Dakota
| | - James M Stevenson
- Department of Pharmacy and Therapeutics, Center for Clinical Pharmaceutical Sciences, University of Pittsburgh School of Pharmacy, Pittsburgh, Pennsylvania
| | - Nicholas Varunok
- Division of Cardiology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Mark R Vesely
- Department of Medicine, University of Maryland, Baltimore, Maryland; Veterans Administration Medical Center, Baltimore, Maryland
| | - Dyson T Wake
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida
| | - Karen E Weck
- Department of Pathology and Laboratory Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Kristin W Weitzel
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida
| | - Russell A Wilke
- Department of Medicine, University of South Dakota, Sanford School of Medicine, Sioux Falls, South Dakota
| | - James Willig
- Division of Cardiovascular Sciences, Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Richard Y Zhao
- Department of Pathology, University of Maryland School of Medicine, Baltimore, Maryland
| | - Rolf P Kreutz
- Department of Medicine, Krannert Institute of Cardiology & Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana
| | - George A Stouffer
- Division of Cardiology and McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Philip E Empey
- Department of Pharmacy and Therapeutics, Center for Clinical Pharmaceutical Sciences, University of Pittsburgh School of Pharmacy, Pittsburgh, Pennsylvania
| | - Nita A Limdi
- Department of Neurology and Hugh Kaul Personalized Medicine Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Alan R Shuldiner
- Department of Medicine, University of Maryland, Baltimore, Maryland
| | - Almut G Winterstein
- Department of Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida; Department of Epidemiology, Colleges of Medicine and Public Health and Health Professions, University of Florida, Gainesville, Florida
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida; Department of Medicine, Division of Cardiovascular Medicine, University of Florida, Gainesville, Florida
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O’Donnell PH, Wadhwa N, Danahey K, Borden BA, Lee SM, Hall JP, Klammer C, Hussain S, Siegler M, Sorrentino MJ, Davis AM, Sacro YA, Nanda R, Polonsky TS, Koyner JL, Burnet DL, Lipstreuer K, Rubin DT, Mulcahy C, Strek ME, Harper W, Cifu AS, Polite B, Patrick-Miller L, Yeo KTJ, Leung EKY, Volchenboum SL, Altman RB, Olopade OI, Stadler WM, Meltzer DO, Ratain MJ. Pharmacogenomics-Based Point-of-Care Clinical Decision Support Significantly Alters Drug Prescribing. Clin Pharmacol Ther 2017; 102:859-869. [PMID: 28398598 PMCID: PMC5636653 DOI: 10.1002/cpt.709] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 03/31/2017] [Accepted: 04/05/2017] [Indexed: 12/22/2022]
Abstract
Changes in behavior are necessary to apply genomic discoveries to practice. We prospectively studied medication changes made by providers representing eight different medicine specialty clinics whose patients had submitted to preemptive pharmacogenomic genotyping. An institutional clinical decision support (CDS) system provided pharmacogenomic results using traffic light alerts: green = genomically favorable, yellow = genomic caution, red = high risk. The influence of pharmacogenomic alerts on prescribing behaviors was the primary endpoint. In all, 2,279 outpatient encounters were analyzed. Independent of other potential prescribing mediators, medications with high pharmacogenomic risk were changed significantly more often than prescription drugs lacking pharmacogenomic information (odds ratio (OR) = 26.2 (9.0-75.3), P < 0.0001). Medications with cautionary pharmacogenomic information were also changed more frequently (OR = 2.4 (1.7-3.5), P < 0.0001). No pharmacogenomically high-risk medications were prescribed during the entire study when physicians consulted the CDS tool. Pharmacogenomic information improved prescribing in patterns aimed at reducing patient risk, demonstrating that enhanced prescription decision-making is achievable through clinical integration of genomic medicine.
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Affiliation(s)
- Peter H. O’Donnell
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, IL, U.S.A
| | - Nisha Wadhwa
- Pritzker School of Medicine, The University of Chicago, Chicago, IL, U.S.A
| | - Keith Danahey
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Center for Research Informatics, The University of Chicago, Chicago, IL, U.S.A
| | - Brittany A. Borden
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Sang Mee Lee
- Department of Health Sciences, The University of Chicago, Chicago, IL, U.S.A
| | - Julianne P. Hall
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Catherine Klammer
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Sheena Hussain
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Mark Siegler
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, IL, U.S.A
- MacLean Center for Clinical Medical Ethics, The University of Chicago, Chicago, IL, U.S.A
| | - Matthew J. Sorrentino
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Andrew M. Davis
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Yasmin A. Sacro
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Rita Nanda
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Tamar S. Polonsky
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Jay L. Koyner
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Deborah L. Burnet
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Kristen Lipstreuer
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - David T. Rubin
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Cathleen Mulcahy
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Mary E. Strek
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, IL, U.S.A
| | - William Harper
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Adam S. Cifu
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Blase Polite
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Linda Patrick-Miller
- Center for Clinical Cancer Genetics, The University of Chicago, Chicago, IL, U.S.A
| | - Kiang-Teck J. Yeo
- Department of Pathology, The University of Chicago, Chicago, IL, U.S.A
| | | | | | - Russ B. Altman
- Departments of Bioengineering, Genetics, and Medicine, Stanford University, Palo Alto, CA, U.S.A
| | | | - Walter M. Stadler
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - David O. Meltzer
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Health and the Social Sciences, The University of Chicago, Chicago, IL, U.S.A
| | - Mark J. Ratain
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, IL, U.S.A
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Luzum JA, Pakyz RE, Elsey AR, Haidar CE, Peterson JF, Whirl-Carrillo M, Handelman SK, Palmer K, Pulley JM, Beller M, Schildcrout JS, Field JR, Weitzel KW, Cooper-DeHoff RM, Cavallari LH, O’Donnell PH, Altman RB, Pereira N, Ratain MJ, Roden DM, Embi PJ, Sadee W, Klein TE, Johnson JA, Relling MV, Wang L, Weinshilboum RM, Shuldiner AR, Freimuth RR. The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Outcomes and Metrics of Pharmacogenetic Implementations Across Diverse Healthcare Systems. Clin Pharmacol Ther 2017; 102:502-510. [PMID: 28090649 PMCID: PMC5511786 DOI: 10.1002/cpt.630] [Citation(s) in RCA: 102] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 01/11/2017] [Indexed: 12/23/2022]
Abstract
Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the National Institutes of Health (NIH) Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real-world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene-drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.
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Affiliation(s)
- Jasmine A. Luzum
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, USA
- Center for Pharmacogenomics, College of Medicine, Ohio State University, Columbus, OH, USA
| | - Ruth E. Pakyz
- Program for Personalized and Genomic Medicine, School of Medicine, University of Maryland, Baltimore, MD, USA
| | - Amanda R. Elsey
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL, USA
| | - Cyrine E. Haidar
- Department of Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - Josh F. Peterson
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | | | - Samuel K. Handelman
- Center for Pharmacogenomics, College of Medicine, Ohio State University, Columbus, OH, USA
| | - Kathleen Palmer
- Program for Personalized and Genomic Medicine, School of Medicine, University of Maryland, Baltimore, MD, USA
| | - Jill M. Pulley
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Marc Beller
- Office of Research Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Jonathan S. Schildcrout
- Department of Statistics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Julie R. Field
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Kristin W. Weitzel
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL, USA
| | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL, USA
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL, USA
| | - Peter H. O’Donnell
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - Russ B. Altman
- Stanford University School of Medicine, Palo Alto, California, USA
| | - Naveen Pereira
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Mark J. Ratain
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - Dan M. Roden
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Peter J. Embi
- Department of Biomedical Informatics, Ohio State University, Columbus, OH, USA
| | - Wolfgang Sadee
- Center for Pharmacogenomics, College of Medicine, Ohio State University, Columbus, OH, USA
- Department of Cancer Biology and Genetics, College of Medicine, Ohio State University, Columbus, OH, USA
| | - Teri E. Klein
- Stanford University School of Medicine, Palo Alto, California, USA
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL, USA
| | - Mary V. Relling
- Department of Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - Liewei Wang
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Richard M. Weinshilboum
- Department of Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Alan R. Shuldiner
- Program for Personalized and Genomic Medicine, School of Medicine, University of Maryland, Baltimore, MD, USA
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Cavallari LH. Personalizing antiplatelet prescribing using genetics for patients undergoing percutaneous coronary intervention. Expert Rev Cardiovasc Ther 2017; 15:581-589. [PMID: 28699807 DOI: 10.1080/14779072.2017.1355236] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Clopidogrel is commonly prescribed with aspirin to reduce the risk for adverse cardiovascular events after percutaneous coronary intervention (PCI). However, there is significant inter-patient variability in clopidogrel response. The CYP2C19 enzyme is involved in the biotransformation of clopidogrel to its pharmacologically active form, and variation in the CYP2C19 gene contributes to clopidogrel response variability. Areas covered. This article describes the impact of CYP2C19 genotype on clopidogrel pharmacokinetics, pharmacodynamics, and effectiveness. Examples of clinical implementation of CYP2C19 genotype-guided antiplatelet therapy for patients undergoing PCI are also described as are emerging outcomes data with this treatment approach. Expert commentary. A large clinical trial evaluating outcomes with CYP2C19 genotype-guided antiplatelet therapy after PCI is on-going. In the meantime, data from pragmatic and observational studies and smaller trials support improved outcomes with genotyping after PCI and use of alternative antiplatelet therapy in patients with a CYP2C19 genotype associated with reduced clopidogrel effectiveness.
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Affiliation(s)
- Larisa H Cavallari
- a Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics , University of Florida College of Pharmacy , Gainesville , FL , USA
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42
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Sperber NR, Carpenter JS, Cavallari LH, J. Damschroder L, Cooper-DeHoff RM, Denny JC, Ginsburg GS, Guan Y, Horowitz CR, Levy KD, Levy MA, Madden EB, Matheny ME, Pollin TI, Pratt VM, Rosenman M, Voils CI, W. Weitzel K, Wilke RA, Ryanne Wu R, Orlando LA. Challenges and strategies for implementing genomic services in diverse settings: experiences from the Implementing GeNomics In pracTicE (IGNITE) network. BMC Med Genomics 2017; 10:35. [PMID: 28532511 PMCID: PMC5441047 DOI: 10.1186/s12920-017-0273-2] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Accepted: 05/10/2017] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND To realize potential public health benefits from genetic and genomic innovations, understanding how best to implement the innovations into clinical care is important. The objective of this study was to synthesize data on challenges identified by six diverse projects that are part of a National Human Genome Research Institute (NHGRI)-funded network focused on implementing genomics into practice and strategies to overcome these challenges. METHODS We used a multiple-case study approach with each project considered as a case and qualitative methods to elicit and describe themes related to implementation challenges and strategies. We describe challenges and strategies in an implementation framework and typology to enable consistent definitions and cross-case comparisons. Strategies were linked to challenges based on expert review and shared themes. RESULTS Three challenges were identified by all six projects, and strategies to address these challenges varied across the projects. One common challenge was to increase the relative priority of integrating genomics within the health system electronic health record (EHR). Four projects used data warehousing techniques to accomplish the integration. The second common challenge was to strengthen clinicians' knowledge and beliefs about genomic medicine. To overcome this challenge, all projects developed educational materials and conducted meetings and outreach focused on genomic education for clinicians. The third challenge was engaging patients in the genomic medicine projects. Strategies to overcome this challenge included use of mass media to spread the word, actively involving patients in implementation (e.g., a patient advisory board), and preparing patients to be active participants in their healthcare decisions. CONCLUSIONS This is the first collaborative evaluation focusing on the description of genomic medicine innovations implemented in multiple real-world clinical settings. Findings suggest that strategies to facilitate integration of genomic data within existing EHRs and educate stakeholders about the value of genomic services are considered important for effective implementation. Future work could build on these findings to evaluate which strategies are optimal under what conditions. This information will be useful for guiding translation of discoveries to clinical care, which, in turn, can provide data to inform continual improvement of genomic innovations and their applications.
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Affiliation(s)
- Nina R. Sperber
- Division of General Internal Medicine, Duke University School of Medicine, Durham, NC USA
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC USA
- VA Health Services Research & Development, Durham VA Health Care System, 411 West Chapel Hill Street, Suite 600, Durham, NC 27701 USA
| | | | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL USA
| | - Laura J. Damschroder
- Implementation Pathways, LLC and VA Ann Arbor Center for Clinical Management Research, Ann Arbor, USA
| | - Rhonda M. Cooper-DeHoff
- University of Florida, College of Pharmacy and Medicine and Center for Pharmacogenomics, Gainesville, USA
| | | | - Geoffrey S. Ginsburg
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC USA
| | - Yue Guan
- University of Maryland School of Medicine, Baltimore, USA
| | | | | | - Mia A. Levy
- Vanderbilt University Medical Center, Nashville, USA
| | - Ebony B. Madden
- National Human Genome Research Institute (NHGRI), Rockville, USA
| | - Michael E. Matheny
- Vanderbilt University Medical Center, Tennessee Valley HealthCare System VA, Nashville, USA
| | - Toni I. Pollin
- University of Maryland School of Medicine, Baltimore, USA
| | | | - Marc Rosenman
- Indiana University School of Nursing, Indianapolis, IN USA
| | - Corrine I. Voils
- William S. Middleton Memorial Veterans Hospital, Madison, WI USA
- Department of Surgery, University of Wisconsin-Madison, Madison, WI USA
| | - Kristen W. Weitzel
- University of Florida, College of Pharmacy and Medicine and Center for Pharmacogenomics, Gainesville, USA
| | - Russell A. Wilke
- Sanford School of Medicine, University of South Dakota, Vermillion, USA
| | - R. Ryanne Wu
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC USA
- Duke University, Duke-National University of Singapore Medical School, 8 College Road, Singapore, 169857 Singapore
| | - Lori A. Orlando
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC USA
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McAllister SL, Sun K, Gross ER. Developing precision medicine for people of East Asian descent. J Biomed Sci 2016; 23:80. [PMID: 27835996 PMCID: PMC5106841 DOI: 10.1186/s12929-016-0299-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Accepted: 11/04/2016] [Indexed: 02/04/2023] Open
Abstract
The goal of precision medicine is to separate patient populations into groups to ultimately provide customized care tailored to patients. In terms of precision medicine, ~540 million people in the world have a genetic variant of the aldehyde dehydrogenase 2 (ALDH2) enzyme causing a flushing response and tachycardia after alcohol consumption. The genetic variant is identified as ALDH2*2 and originates from East Asian descendants of the Han Chinese. The variant is particularly important to consider when discussing lifestyle choices with patients in terms of risk for developing specific diseases, preventative screening, and selection of medications for treatment. Here we provide examples why patients with an ALDH2*2 variant need more individualized medical management which is becoming a more standard practice in the precision medicine era.
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Affiliation(s)
- Stacy L McAllister
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, 300 Pasteur Drive, Grant Building, Room S290, Stanford, CA, 94305, USA
| | - Katherine Sun
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, 300 Pasteur Drive, Grant Building, Room S290, Stanford, CA, 94305, USA
| | - Eric R Gross
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, 300 Pasteur Drive, Grant Building, Room S290, Stanford, CA, 94305, USA.
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Cavallari LH, Duarte JD. Clopidogrel pharmacogenetics: from evidence to implementation. Future Cardiol 2016; 12:511-4. [PMID: 27539287 DOI: 10.2217/fca-2016-0045] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Affiliation(s)
- Larisa H Cavallari
- Department of Pharmacotherapy & Translational Research & Center for Pharmacogenomics, University of Florida, 1333 Center Drive, PO Box 100486, Gainesville, FL 32610, USA
| | - Julio D Duarte
- Department of Pharmacotherapy & Translational Research & Center for Pharmacogenomics, University of Florida, 1333 Center Drive, PO Box 100486, Gainesville, FL 32610, USA
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Abstract
Certain antithrombotic drugs exhibit high patient-to-patient variability that significantly impacts the safety and efficacy of therapy. Pharmacogenetics offers the possibility of tailoring drug treatment to patients based on individual genotypes, and this type of testing has been recommended for 2 oral antithrombotic agents, warfarin and clopidogrel, to influence use and guide dosing. Limited studies have identified polymorphisms that affect the metabolism and activity of newer oral antithrombotic drugs, without clear evidence of the clinical relevance of such polymorphisms. This article provides an overview of the current status of pharmacogenetics in oral antithrombotic therapy.
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Affiliation(s)
- Cheryl L Maier
- Department of Pathology and Laboratory Medicine, Emory University Hospital, Emory University School of Medicine, 1364 Clifton Road Northeast, Atlanta, GA 30322, USA.
| | - Alexander Duncan
- Department of Pathology and Laboratory Medicine, Emory University Hospital, Emory University School of Medicine, 1364 Clifton Road Northeast, Atlanta, GA 30322, USA
| | - Charles E Hill
- Department of Pathology and Laboratory Medicine, Emory University Hospital, Emory University School of Medicine, 1364 Clifton Road Northeast, Atlanta, GA 30322, USA
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