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Preys CL, Blout Zawatsky CL, Massmann A, Heukelom JV, Green RC, Hajek C, Hickingbotham MR, Zoltick ES, Schultz A, Christensen KD. Attitudes about pharmacogenomic testing vary by healthcare specialty. Pharmacogenomics 2023; 24:539-549. [PMID: 37458095 PMCID: PMC10621761 DOI: 10.2217/pgs-2023-0039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023] Open
Abstract
Aim: To understand how attitudes toward pharmacogenomic (PGx) testing among healthcare providers varies by specialty. Methods: Providers reported comfort ordering PGx testing and its perceived utility on web-based surveys before and after genetics education. Primary quantitative analyses compared primary care providers (PCPs) to specialty providers at both timepoints. Results: PCPs were more likely than specialty care providers to rate PGx testing as useful at both timepoints. Education increased comfort ordering PGx tests, with larger improvements among PCPs than specialty providers. Over 90% of cardiology and internal medicine providers rated PGx testing as useful at pre- and post-education. Conclusion: PCPs overwhelmingly perceive PGx to be useful, and provider education is particularly effective for improving PCPs' confidence. Education for all specialties will be essential to ensure appropriate integration into routine practice.
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Affiliation(s)
- Charlene L Preys
- MGH Institute of Health Professions, Charlestown, MA 02129, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Carrie L Blout Zawatsky
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
- Ariadne Labs, Boston, MA 02215, USA
| | - Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermilion, SD 57069, USA
| | - Joel Van Heukelom
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermilion, SD 57069, USA
| | - Robert C Green
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
- Ariadne Labs, Boston, MA 02215, USA
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Catherine Hajek
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Helix OpCo, LLC, San Diego, CA 92121, USA
| | - Madison R Hickingbotham
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Emilie S Zoltick
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - April Schultz
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermilion, SD 57069, USA
| | - Kurt D Christensen
- Ariadne Labs, Boston, MA 02215, USA
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02115, USA
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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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Haidar CE, Crews KR, Hoffman JM, Relling MV, Caudle KE. Advancing Pharmacogenomics from Single-Gene to Preemptive Testing. Annu Rev Genomics Hum Genet 2022; 23:449-473. [PMID: 35537468 PMCID: PMC9483991 DOI: 10.1146/annurev-genom-111621-102737] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.
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Affiliation(s)
- Cyrine E Haidar
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kristine R Crews
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - James M Hoffman
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
- Office of Quality and Safety, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Mary V Relling
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kelly E Caudle
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
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Perera UT, Heeney C, Sheikh A. Policy parameters for optimising hospital ePrescribing: An exploratory literature review of selected countries of the Organisation for Economic Co-operation and Development. Digit Health 2022; 8:20552076221085074. [PMID: 35340903 PMCID: PMC8941697 DOI: 10.1177/20552076221085074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 02/16/2022] [Indexed: 11/16/2022] Open
Abstract
Objective Electronic prescribing systems offer considerable opportunities to enhance
the safety, effectiveness and efficiency of prescribing and medicines
management decisions but, despite considerable investments in health IT
infrastructure and healthcare professional training, realising these
benefits continues to prove challenging. How systems are customised and
configured to achieve optimal functionality is an increasing focus for
policymakers. We sought to develop an overview of the policy landscape
currently supporting optimisation of hospital ePrescribing systems in
economically developed countries with a view to deriving lessons for the
United Kingdom (UK). Methods We conducted a review of research literature and policy documents pertaining
to optimisation of ePrescribing within hospitals across Organisation for
Economic Co-operation and Development (OECD) countries on Embase, Medline,
National Institute for Health (NIH), Google Scholar databases from 2010 to
2020 and the websites of organisations with international and national
health policy interests in digital health and ePrescribing. We designed a
typology of policies targeting optimisation of ePrescribing systems that
provides an overview of evidence relating to the level at which policy is
set, the aims and the barriers encountered in enacting these policies. Results Our database searches retrieved 11 relevant articles and other web resources
mainly from North America and Western Europe. We identified very few
countries with a national level strategy for optimisation of ePrescribing in
hospitals. There were hotspots of digital maturity in relation to
ePrescribing at institutional, specialisation, regional and national levels
in the US and Europe. We noted that such countries with digital maturity
fostered innovations such as patient involvement. Conclusions We found that, whilst helpful to achieve certain aims, coordinated strategies
within and across countries for optimisation of ePrescribing systems are
rare, even in countries with well-established ePrescribing and digital
health infrastructures. There is at present little policy focus on
maximising the utility of ePrescribing systems.
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Affiliation(s)
- Uditha T Perera
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, UK
| | - Catherine Heeney
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, UK
| | - Aziz Sheikh
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, UK
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5
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Pardiñas AF, Owen MJ, Walters JTR. Pharmacogenomics: A road ahead for precision medicine in psychiatry. Neuron 2021; 109:3914-3929. [PMID: 34619094 DOI: 10.1016/j.neuron.2021.09.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 08/05/2021] [Accepted: 09/09/2021] [Indexed: 12/11/2022]
Abstract
Psychiatric genomics is providing insights into the nature of psychiatric conditions that in time should identify new drug targets and improve patient care. Less attention has been paid to psychiatric pharmacogenomics research, despite its potential to deliver more rapid change in clinical practice and patient outcomes. The pharmacogenomics of treatment response encapsulates both pharmacokinetic ("what the body does to a drug") and pharmacodynamic ("what the drug does to the body") effects. Despite early optimism and substantial research in both these areas, they have to date made little impact on clinical management in psychiatry. A number of bottlenecks have hampered progress, including a lack of large-scale replication studies, inconsistencies in defining valid treatment outcomes across experiments, a failure to routinely incorporate adverse drug reactions and serum metabolite monitoring in study designs, and inadequate investment in the longitudinal data collections required to demonstrate clinical utility. Nonetheless, advances in genomics and health informatics present distinct opportunities for psychiatric pharmacogenomics to enter a new and productive phase of research discovery and translation.
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Affiliation(s)
- Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff CF24 4HQ, UK
| | - Michael J Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff CF24 4HQ, UK.
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff CF24 4HQ, UK
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Juskewitch JE, Tauscher CD, Moldenhauer SK, Schieber JE, Jacob EK, DiGuardo MA. To Give or Not to Give: RhD Immunoglobulin for an RHD * 39 Pregnant Woman with Sickle Cell Disease. Transfus Med Hemother 2021; 48:244-249. [PMID: 34539319 DOI: 10.1159/000512644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 10/27/2020] [Indexed: 11/19/2022] Open
Abstract
Introduction Patients with sickle cell disease (SCD) have repeated episodes of red blood cell (RBC) sickling and microvascular occlusion that manifest as pain crises, acute chest syndrome, and chronic hemolysis. These clinical sequelae usually increase during pregnancy. Given the racial distribution of SCD, patients with SCD are also more likely to have rarer RBC antigen genotypes than RBC donor populations. We present the management and clinical outcome of a 21-year-old pregnant woman with SCD and an RHD*39 (RhD[S103P], G-negative) variant. Case Presentation Ms. S is B positive with a reported history of anti-D, anti-C, and anti-E alloantibodies (anti-G testing unknown). Genetic testing revealed both an RHD*39 and homozygous partial RHCE*ceVS.02 genotype. Absorption/elution testing confirmed the presence of anti-G, anti-C, and anti-E alloantibodies but could not definitively determine the presence/absence of an anti-D alloantibody. Ms. S desired to undergo elective pregnancy termination and the need for postprocedural RhD immunoglobulin (RhIG) was posed. Given that only the G antigen site is changed in an RHD*39 genotype and the potential risk of RhIG triggering a hyperhemolytic episode in an SCD patient, RhIG was not administered. There were no procedural complications. Follow-up testing at 10 weeks showed no increase in RBC alloantibody strength. Discussion/Conclusion Ms. S represents a rare RHD*39 and partial RHCE*ceVS.02 genotype which did not further alloimmunize in the absence of RhIG administration. Her case also highlights the importance of routine anti-G alloantibody testing in women of childbearing age with apparent anti-D and anti-C alloantibodies.
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Affiliation(s)
| | - Craig D Tauscher
- Division of Transfusion Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Eapen K Jacob
- Division of Transfusion Medicine, Mayo Clinic, Rochester, Minnesota, USA
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Haidar CE, Petry N, Oxencis C, Douglas JS, Hoffman JM. ASHP Statement on the Pharmacist's Role in Clinical Pharmacogenomics. Am J Health Syst Pharm 2021; 79:704-707. [PMID: 34487145 DOI: 10.1093/ajhp/zxab339] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Affiliation(s)
| | - Natasha Petry
- North Dakota State University, Sanford Health, Fargo, ND, USA
| | | | - Janine S Douglas
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Young J, Bhattacharya K, Ramachandran S, Lee A, Bentley JP. Rates of genetic testing in patients prescribed drugs with pharmacogenomic information in FDA-approved labeling. THE PHARMACOGENOMICS JOURNAL 2021; 21:318-325. [PMID: 33589791 PMCID: PMC7883752 DOI: 10.1038/s41397-021-00211-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 12/08/2020] [Accepted: 01/15/2021] [Indexed: 12/21/2022]
Abstract
This study examined rates of genetic testing in two cohorts of publicly insured individuals who have newly prescribed medication with FDA pharmacogenomic labeling guidance. Genetic testing was rare (4.4% and 10.5% in Medicaid and Medicare cohorts, respectively) despite the fact that all participants selected were taking medications that contained pharmacogenomic labeling information. When testing was conducted it was typically done before the initial use of a target medication. Factors that emerged as predictors of the likelihood of undergoing genetic testing included White ethnicity (vs. Black), female gender, and age. Cost analyses indicated higher expenditures in groups receiving genetic testing vs. matched comparators with no genetic testing, as well as disparities between proactively and reactively tested groups (albeit in opposite directions across cohorts). Results are discussed in terms of the possible reasons for the low base rate of testing, mechanisms of increased cost, and barriers to dissemination and implementation of these tests.
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Affiliation(s)
- John Young
- Department of Psychology, University of Mississippi, University, MS, USA.
| | - Kaustuv Bhattacharya
- Department of Pharmacy Administration, University of Mississippi, University, MS, USA
| | - Sujith Ramachandran
- Department of Pharmacy Administration, University of Mississippi, University, MS, USA
| | - Aaron Lee
- Department of Psychology, University of Mississippi, University, MS, USA
| | - John P Bentley
- Department of Pharmacy Administration, University of Mississippi, University, MS, USA
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9
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Ramsey LB, Ong HH, Schildcrout JS, Shi Y, Tang LA, Hicks JK, El Rouby N, Cavallari LH, Tuteja S, Aquilante CL, Beitelshees AL, Lemkin DL, Blake KV, Williams H, Cimino JJ, Davis BH, Limdi NA, Empey PE, Horvat CM, Kao DP, Lipori GP, Rosenman MB, Skaar TC, Teal E, Winterstein AG, Owusu Obeng A, Salyakina D, Gupta A, Gruber J, McCafferty-Fernandez J, Bishop JR, Rivers Z, Benner A, Tamraz B, Long-Boyle J, Peterson JF, Van Driest SL. Prescribing Prevalence of Medications With Potential Genotype-Guided Dosing in Pediatric Patients. JAMA Netw Open 2020; 3:e2029411. [PMID: 33315113 PMCID: PMC7737091 DOI: 10.1001/jamanetworkopen.2020.29411] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 09/28/2020] [Indexed: 12/17/2022] Open
Abstract
Importance Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation. Objective To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions. Design, Setting, and Participants This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020. Exposures Prescription of 38 level A medications based on electronic health records. Main Outcomes and Measures Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally. Results Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes. Conclusions and Relevance These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.
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Affiliation(s)
- Laura B. Ramsey
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio
- Divisions of Research in Patient Services and Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
| | - Henry H. Ong
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Yaping Shi
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Leigh Anne Tang
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - J. Kevin Hicks
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Nihal El Rouby
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville
- James Winkle College of Pharmacy, University of Cincinnati, Cincinnati, Ohio
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville
| | - Sony Tuteja
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | | | | - Daniel L. Lemkin
- Department of Emergency Medicine, University of Maryland, Baltimore
| | - Kathryn V. Blake
- Center for Pharmacogenomics and Translational Research, Nemours Children’s Health System, Jacksonville, Florida
| | - Helen Williams
- Nemours Research Institute, Nemours Children’s Health System, Jacksonville, Florida
| | | | | | - Nita A. Limdi
- Department of Neurology, University of Alabama at Birmingham
| | - Philip E. Empey
- Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Christopher M. Horvat
- Department of Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - David P. Kao
- Department of Medicine, School of Medicine, University of Colorado, Aurora
| | - Gloria P. Lipori
- University of Florida Health and University of Florida Health Sciences Center, Gainesville
| | - Marc B. Rosenman
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis
- Department of Pediatrics, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois
| | - Todd C. Skaar
- Department of Medicine, Indiana University School of Medicine, Indianapolis
| | | | - Almut G. Winterstein
- Department of Pharmaceutical Outcomes and Policy and Center for Drug Evaluation and Safety, University of Florida, Gainesville
| | - Aniwaa Owusu Obeng
- The Charles Bronfman Institute for Personalized Medicine, Departments of Medicine and Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Daria Salyakina
- Personalized Medicine Initiative, Nicklaus Children’s Health System, Miami, Florida
| | - Apeksha Gupta
- Personalized Medicine Initiative, Nicklaus Children’s Health System, Miami, Florida
| | - Joshua Gruber
- Personalized Medicine Initiative, Nicklaus Children’s Health System, Miami, Florida
| | | | - Jeffrey R. Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis
| | - Zach Rivers
- Department of Pharmaceutical Care and Health Systems, University of Minnesota College of Pharmacy, Minneapolis
| | - Ashley Benner
- Clinical and Translational Science Institute, University of Minnesota, Minneapolis
| | - Bani Tamraz
- School of Pharmacy, University of California, San Francisco
| | | | - Josh F. Peterson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee
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