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Clinical implementation of drug metabolizing gene-based therapeutic interventions worldwide. Hum Genet 2021; 141:1137-1157. [PMID: 34599365 DOI: 10.1007/s00439-021-02369-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/09/2021] [Indexed: 02/05/2023]
Abstract
Over the last few years, the field of pharmacogenomics has gained considerable momentum. The advances of new genomics and bioinformatics technologies propelled pharmacogenomics towards its implementation in the clinical setting. Since 2007, and especially the last-5 years, many studies have focused on the clinical implementation of pharmacogenomics while identifying obstacles and proposed strategies and approaches for overcoming them in the real world of primary care as well as outpatients and inpatients clinics. Here, we outline the recent pharmacogenomics clinical implementation projects and provide details of the study designs, including the most predominant and innovative, as well as clinical studies worldwide that focus on outpatients and inpatient clinics, and primary care. According to these studies, pharmacogenomics holds promise for improving patients' health in terms of efficacy and toxicity, as well as in their overall quality of life, while simultaneously can contribute to the minimization of healthcare expenditure.
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Cohn I, Manshaei R, Liston E, Okello JBA, Khan R, Curtis MR, Krupski AJ, Jobling RK, Kalbfleisch K, Paton TA, Reuter MS, Hayeems RZ, Verstegen RHJ, Goldman A, Kim RH, Ito S. Assessment of the Implementation of Pharmacogenomic Testing in a Pediatric Tertiary Care Setting. JAMA Netw Open 2021; 4:e2110446. [PMID: 34037732 PMCID: PMC8155824 DOI: 10.1001/jamanetworkopen.2021.10446] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
IMPORTANCE Pharmacogenomic (PGx) testing provides preemptive pharmacotherapeutic guidance regarding the lack of therapeutic benefit or adverse drug reactions of PGx targeted drugs. Pharmacogenomic information is of particular value among children with complex medical conditions who receive multiple medications and are at higher risk of developing adverse drug reactions. OBJECTIVES To assess the implementation outcomes of a PGx testing program comprising both a point-of-care model that examined targeted drugs and a preemptive model informed by whole-genome sequencing that evaluated a broad range of drugs for potential therapy among children in a pediatric tertiary care setting. DESIGN, SETTING, AND PARTICIPANTS This cohort study was conducted at The Hospital for Sick Children in Toronto, Ontario, from January 2017 to September 2020. Pharmacogenomic analyses were performed among 172 children who were categorized into 2 groups: a point-of-care cohort and a preemptive cohort. The point-of-care cohort comprised 57 patients referred to the consultation clinic for planned therapy with PGx targeted drugs and/or for adverse drug reactions, including lack of therapeutic benefit, after the receipt of current or past medications. The preemptive cohort comprised 115 patients who received exploratory whole-genome sequencing-guided PGx testing for their heart conditions from the cardiac genome clinic at the Ted Rogers Centre for Heart Research. EXPOSURES Patients received PGx analysis of whole-genome sequencing data and/or multiplex genotyping of 6 pharmacogenes (CYP2C19, CYP2C9, CYP2D6, CYP3A5, VKORC1, and TPMT) that have established PGx clinical guidelines. MAIN OUTCOMES AND MEASURES The number of patients for whom PGx test results warranted deviation from standard dosing regimens. RESULTS A total of 172 children (mean [SD] age, 8.5 [5.6] years; 108 boys [62.8%]) were enrolled in the study. In the point-of-care cohort, a median of 2 target genes (range, 1-5 genes) were investigated per individual, with CYP2C19 being the most frequently examined; genotypes in 21 of 57 children (36.8%) were incompatible with standard treatment regimens. As expected from population allelic frequencies, among the 115 children in the whole-genome sequencing-guided preemptive cohort, 92 children (80.0%) were recommended to receive nonstandard treatment regimens for potential drug therapies based on their 6-gene pharmacogenetic profile. CONCLUSIONS AND RELEVANCE In this cohort study, among both the point-of-care and preemptive cohorts, the multiplex PGx testing program provided dosing recommendations that deviated from standard regimens at an overall rate that was similar to the population frequencies of relevant variants.
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Affiliation(s)
- Iris Cohn
- Division of Clinical Pharmacology and Toxicology, Department of Paediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Roozbeh Manshaei
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Eriskay Liston
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - John B. A. Okello
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Reem Khan
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Meredith R. Curtis
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Abby J. Krupski
- Division of Clinical Pharmacology and Toxicology, Department of Paediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Rebekah K. Jobling
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, Ontario, Canada
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Genome Diagnostics, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Kelsey Kalbfleisch
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, Ontario, Canada
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Tara A. Paton
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Miriam S. Reuter
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, Ontario, Canada
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Canada’s Genomic Enterprise (CGEn), The Hospital for Sick Children, Toronto, Ontario, Canada
- Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Robin Z. Hayeems
- Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Ontario, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Ruud H. J. Verstegen
- Division of Clinical Pharmacology and Toxicology, Department of Paediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
- Division of Rheumatology, Department of Paediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | | | - Raymond H. Kim
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, Ontario, Canada
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Fred A. Litwin Family Centre in Genetic Medicine, University Health Network, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Shinya Ito
- Division of Clinical Pharmacology and Toxicology, Department of Paediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
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A model-based cost-effectiveness analysis of pharmacogenomic panel testing in cardiovascular disease management: preemptive, reactive, or none? Genet Med 2020; 23:461-470. [PMID: 33041335 PMCID: PMC7935716 DOI: 10.1038/s41436-020-00995-w] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 09/23/2020] [Accepted: 09/24/2020] [Indexed: 11/15/2022] Open
Abstract
Purpose Pharmacogenomics (PGx) studies how inherited genetic variations in individuals affect drug absorption, distribution, and metabolism. PGx panel testing can potentially help improve efficiency and accuracy in individualizing therapy. This study compared the cost-effectiveness between preemptive PGx panel testing, reactive PGx panel testing and usual care (no testing) in cardiovascular disease management. Methods We developed a decision analytic model from the US payer’s perspective for a hypothetical cohort of 10,000 patients ≥45 years old, using a short-term decision tree and long-term Markov model. The testing panel included the following gene–drug pairs: CYP2C19–clopidogrel, CYP2C9/VKORC1–warfarin, and SLCO1B1–statins with 30 test-return days. Costs were reported in 2019 US dollars and effectiveness was measured in quality-adjusted life years (QALYs). The primary outcome was incremental cost-effectiveness ratio (ICER = ΔCost/ΔQALY), assuming 3% discount rate for costs and QALYs. Scenario and probabilistic sensitivity analyses were performed to assess the impact of demographics, risk level, and follow-up timeframe. Results Preemptive testing was found to be cost-effective compared with usual care (ICER $86,227/QALY) at the willingness-to-pay threshold of $100,000/QALY while reactive testing was not (ICER $148,726/QALY). Sensitivity analyses suggested that our cost-effectiveness results were sensitive to longer follow-up, and the age group 45–64 years. Conclusion Compared with usual care, preemptive PGx panel testing was cost-effective in cardiovascular disease management.
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Ma HC, Chen GJ, Huang F, Dong YB. Homochiral Covalent Organic Framework for Catalytic Asymmetric Synthesis of a Drug Intermediate. J Am Chem Soc 2020; 142:12574-12578. [DOI: 10.1021/jacs.0c04722] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Affiliation(s)
- Hui-Chao Ma
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, P. R. China
| | - Gong-Jun Chen
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, P. R. China
| | - Fang Huang
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, P. R. China
| | - Yu-Bin Dong
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, P. R. China
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Zhu Y, Swanson KM, Rojas RL, Wang Z, St Sauver JL, Visscher SL, Prokop LJ, Bielinski SJ, Wang L, Weinshilboum R, Borah BJ. Systematic review of the evidence on the cost-effectiveness of pharmacogenomics-guided treatment for cardiovascular diseases. Genet Med 2019; 22:475-486. [PMID: 31591509 PMCID: PMC7056639 DOI: 10.1038/s41436-019-0667-y] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 09/23/2019] [Indexed: 02/08/2023] Open
Abstract
PURPOSE To examine the evidence on the cost-effectiveness of implementing pharmacogenomics (PGx) in cardiovascular disease (CVD) care. METHODS We conducted a systematic review using multiple databases from inception to 2018. The titles and abstracts of cost-effectiveness studies on PGx-guided treatment in CVD care were screened, and full texts were extracted. RESULTS We screened 909 studies and included 46 to synthesize. Acute coronary syndrome and atrial fibrillation were the predominantly studied conditions (59%). Most studies (78%) examined warfarin-CYP2C9/VKORC1 or clopidogrel-CYP2C19. A payer's perspective was commonly used (39%) for cost calculations, and most studies (46%) were US-based. The majority (67%) of the studies found PGx testing to be cost-effective in CVD care, but cost-effectiveness varied across drugs and conditions. Two studies examined PGx panel testing, of which one examined pre-emptive testing strategies. CONCLUSION We found mixed evidence on the cost-effectiveness of PGx in CVD care. Supportive evidence exists for clopidogrel-CYP2C19 and warfarin-CYP2C9/VKORC1, but evidence is limited in other drug-gene combinations. Gaps persist, including unclear explanation of perspective and cost inputs, underreporting of study design elements critical to economic evaluations, and limited examination of PGx panel and pre-emptive testing for their cost-effectiveness. This review identifies the need for further research on economic evaluations of PGx implementation.
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Affiliation(s)
- Ye Zhu
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.,Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Kristi M Swanson
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - Ricardo L Rojas
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Zhen Wang
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.,Evidence-Based Practice Center, Mayo Clinic, Rochester, MN, USA
| | - Jennifer L St Sauver
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.,Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Sue L Visscher
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - Larry J Prokop
- Library Public Services, Mayo Clinic, Rochester, MN, USA
| | - Suzette J Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Liewei Wang
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Richard Weinshilboum
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Bijan J Borah
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA. .,Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
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Alshabeeb MA, Deneer VHM, Khan A, Asselbergs FW. Use of Pharmacogenetic Drugs by the Dutch Population. Front Genet 2019; 10:567. [PMID: 31312209 PMCID: PMC6614185 DOI: 10.3389/fgene.2019.00567] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 05/29/2019] [Indexed: 12/27/2022] Open
Abstract
Introduction The Dutch Pharmacogenetics Working Group (DPWG) indicated a list of actionable genotypes that affect patients’ response to more 50 drugs; these drugs which show variable effects based on patients’ genetic traits were named as pharmacogenetics (PGX) drugs. Preemptive genetic testing before using these drugs may protect certain patients from serious adverse reactions and could help in avoiding treatment failures. The objectives of this study include identifying the rate of PGX drug usage among Dutch population, estimating the level of users who carry the actionable genotypes and determining the main genes involved in drug’s effect variability. Methods Usage of PGX drugs over 2011–2017 by the insured population (an average of 11.4 million) in outpatient clinics in Netherlands was obtained from the publically available GIP databank. The data of 45 drugs were analyzed and their interactions with selected pharmacogenes were estimated. Frequency of actionable genotypes of 249 Dutch parents was obtained from the public database: Genome of Netherlands (GoNL), to identify the pattern of genetic characteristics of Dutch population. Results Over a 7 year period, 51.3 million exposures of patients to PGX drugs were reported with an average of 5.3 exposures per each drug user. One quarterof the exposures (12.4 million) are predicted to be experienced by individuals with actionable genotypes (risky exposures). Up to 60% of the risky exposures (around 7.5 million) were related to drugs metabolized by CYP2D6. SLCO1B1, and CYP2C19 were also identified among the top genes affecting response of drugs users (involved in about 22 and 12.4% of the risky exposures, respectively). Cardiovascular medications were the top prescribed PGX drug class (43%), followed by gastroenterology (29%) and psychiatry/neurology medications (15%). Women use more PGX drugs than men (55.8 vs. 44.2%, respectively) with the majority (84%) of users in both sexes are above 45 years. Conclusion PGX drugs are commonly used in Netherlands. Preemptive panel testing for CYP2D6, SLCO1B1, and CYP2C19 only could be useful to predict 95% of vulnerable patients’ exposures to PGX drugs. Future studies to assess the economic impact of preemptive panel testing on patients of older age are suggested.
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Affiliation(s)
- Mohammad A Alshabeeb
- Medical Genomics Research Department, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.,King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.,Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Vera H M Deneer
- Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht, Netherlands
| | - Amjad Khan
- Medical Genomics Research Department, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.,King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
| | - Folkert W Asselbergs
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,Faculty of Population Health Sciences, Institute of Cardiovascular Science, University College London, London, United Kingdom.,Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom
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Fulton CR, Zang Y, Desta Z, Rosenman MB, Holmes AM, Decker BS, Zhang Y, T Callaghan J, Pratt VM, Levy KD, Gufford BT, Dexter PR, Skaar TC, Eadon MT. Drug-gene and drug-drug interactions associated with tramadol and codeine therapy in the INGENIOUS trial. Pharmacogenomics 2019; 20:397-408. [PMID: 30784356 DOI: 10.2217/pgs-2018-0205] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Background: Tramadol and codeine are metabolized by CYP2D6 and are subject to drug-gene and drug-drug interactions. Methods: This interim analysis examined prescribing behavior and efficacy in 102 individuals prescribed tramadol or codeine while receiving pharmaco-genotyping as part of the INGENIOUS trial (NCT02297126). Results: Within 60 days of receiving tramadol or codeine, clinicians more frequently prescribed an alternative opioid in ultrarapid and poor metabolizers (odds ratio: 19.0; 95% CI: 2.8-160.4) as compared with normal or indeterminate metabolizers (p = 0.01). After adjusting the CYP2D6 activity score for drug-drug interactions, uncontrolled pain was reported more frequently in individuals with reduced CYP2D6 activity (odds ratio: 0.50; 95% CI: 0.25-0.94). Conclusion: Phenoconversion for drug-drug and drug-gene interactions is an important consideration in pharmacogenomic implementation; drug-drug interactions may obscure the potential benefits of genotyping.
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Affiliation(s)
- Cathy R Fulton
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA.,Department of Health Informatics, Indiana University School of Informatics and Computing, Indianapolis, IN 46202, USA
| | - Yong Zang
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Zeruesenay Desta
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Marc B Rosenman
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA.,Ann & Robert H Lurie Children's Hospital of Chicago, Chicago, IL 60611, USA.,Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Ann M Holmes
- Richard M Fairbanks School of Public Health, Indiana University-Purdue University Indianapolis, IN 46202, USA
| | - Brian S Decker
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Yifei Zhang
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - John T Callaghan
- Regenstrief Institute for Health Care, Indianapolis, IN 46202, USA
| | - Victoria M Pratt
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Kenneth D Levy
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Brandon T Gufford
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Paul R Dexter
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA.,Richard L Roudebush Veteran Affairs Medical Center, Indianapolis, IN 46202, USA
| | - Todd C Skaar
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
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Knisely MR, Carpenter JS, Broome ME, Holmes AM, Von Ah D, Skaar T, Draucker CB. Medication Exposure Patterns in Primary Care Patients Prescribed Pharmacogenetically Actionable Opioids. QUALITATIVE REPORT (ONLINE) 2018; 23:1861-1875. [PMID: 31355374 PMCID: PMC6660172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Current approaches to assessing medication exposure fail to capture the complexity of the phenomenon and the context in which it occurs. This study's purpose was to develop a typology of subgroups of patients who share common patterns of medication exposure. To create the typology, we used an exemplar sample of 30 patients in a large public healthcare system who had been prescribed the pharmacogenetically actionable opioids codeine or tramadol. Data related to medication exposure were drawn from large data repositories. Using a person-oriented qualitative approach, eight subgroups of patients who shared common patterns of medication exposure were identified. The subgroups had one of five opioid prescription patterns (i.e., singular, episodic, switching, sustained, multiplex), and one of three types of primary foci of medical care (i.e., pain, comorbidities, both). The findings reveal medication exposure patterns that are dynamic, multidimensional, and complex, and the typology offers an innovative approach to assessing medication exposure.
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Affiliation(s)
| | | | | | | | | | - Todd Skaar
- Indiana University, Indianapolis, Indiana, USA
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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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Moyer AM, Caraballo PJ. The challenges of implementing pharmacogenomic testing in the clinic. Expert Rev Pharmacoecon Outcomes Res 2017; 17:567-577. [PMID: 28949250 DOI: 10.1080/14737167.2017.1385395] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Pharmacogenomic testing has the potential to greatly benefit patients by enabling personalization of medication management, ensuring better efficacy and decreasing the risk of side effects. However, to fully realize the potential of pharmacogenomic testing, there are several important issues that must be addressed. Areas covered: In this expert review we discuss current challenges impacting the implementation of pharmacogenomic testing in the clinical practice. We emphasize issues related to testing methods, reporting of the results, test selection, clinical interpretation of the results, cost-effectiveness, and the long-term use of pharmacogenomic results in clinical practice. We identify opportunities and future directions to facilitate clinical implementation. Expert commentary: Several key elements are necessary to optimally integrate pharmacogenomic testing into clinical practice. Collaborative efforts among laboratories are needed to improve standardization of testing and reporting of the results. Clinicians need educational opportunities to improve understanding of which test to order and how to interpret the results. The electronic health records and other clinical systems need to improve their storage of the pharmacogenomics test results and interoperability to facilitate the use of clinically actionable results to improve patient care.
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Affiliation(s)
- Ann M Moyer
- a Department of Laboratory Medicine and Pathology , Mayo Clinic , Rochester , MN , USA
| | - Pedro J Caraballo
- b Department of Medicine , Mayo Clinic , Rochester , MN , USA.,c Center for Translational Informatics and Knowledge Management, Mayo Clinic , Rochester , MN , USA
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12
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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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13
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Preemptive Panel-Based Pharmacogenetic Testing: The Time is Now. Pharm Res 2017; 34:1551-1555. [PMID: 28466392 DOI: 10.1007/s11095-017-2163-x] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 04/06/2017] [Indexed: 01/06/2023]
Abstract
While recent discoveries have paved the way for the use of genotype-guided prescribing in some clinical environments, significant debate persists among clinicians and researchers about the optimal approach to pharmacogenetic testing in clinical practice. One crucial factor in this debate surrounds the timing and methodology of genotyping, specifically whether genotyping should be performed reactively for targeted genes when a single drug is prescribed, or preemptively using a panel-based approach prior to drug prescribing. While early clinical models that employed a preemptive approach were largely developed in academic health centers through multidisciplinary efforts, increasing examples of pharmacogenetic testing are emerging in community-based and primary care practice environments. However, educational and practice-based resources for these clinicians remain largely nonexistent. As such, there is a need for the health care system to shift its focus from debating about preemptive genotyping to developing and disseminating needed resources to equip frontline clinicians for clinical implementation of pharmacogenetics. Providing tools and guidance to support these emerging models of care will be essential to support the thoughtful, evidence-based use of pharmacogenetic information in diverse clinical practice environments. Specifically, the creation of efficient and accurate point-of-care resources, practice-based tools, and clinical models is needed, along with identification and dissemination of sustainable avenues for pharmacogenetic test reimbursement.
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14
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van der Wouden CH, Cambon-Thomsen A, Cecchin E, Cheung KC, Dávila-Fajardo CL, Deneer VH, Dolžan V, Ingelman-Sundberg M, Jönsson S, Karlsson MO, Kriek M, Mitropoulou C, Patrinos GP, Pirmohamed M, Samwald M, Schaeffeler E, Schwab M, Steinberger D, Stingl J, Sunder-Plassmann G, Toffoli G, Turner RM, van Rhenen MH, Swen JJ, Guchelaar HJ. Implementing Pharmacogenomics in Europe: Design and Implementation Strategy of the Ubiquitous Pharmacogenomics Consortium. Clin Pharmacol Ther 2017; 101:341-358. [DOI: 10.1002/cpt.602] [Citation(s) in RCA: 186] [Impact Index Per Article: 26.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Revised: 12/12/2016] [Accepted: 12/13/2016] [Indexed: 12/14/2022]
Affiliation(s)
- CH van der Wouden
- Department of Clinical Pharmacy and Toxicology; Leiden University Medical Center; Leiden The Netherlands
| | - A Cambon-Thomsen
- UMR Inserm U1027 and Université de Toulouse III Paul Sabatier; Toulouse France
| | - E Cecchin
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico; National Cancer Institute; Aviano Italy
| | - KC Cheung
- Royal Dutch Pharmacists Association (KNMP); The Hague The Netherlands
| | - CL Dávila-Fajardo
- Department of Clinical Pharmacy, Granada University Hospital; Institute for Biomedical Research; Granada Spain
| | - VH Deneer
- Department of Clinical Pharmacy; St Antonius Hospital; Nieuwegein The Netherlands
| | - V Dolžan
- Pharmacogenetics Laboratory, Institute of Biochemistry, Faculty of Medicine; University of Ljubljana; Slovenia
| | - M Ingelman-Sundberg
- Department of Physiology and Pharmacology, Section of Pharmacogenetics; Karolinska Institutet; Stockholm Sweden
| | - S Jönsson
- Department of Pharmaceutical Biosciences; Uppsala University; Uppsala Sweden
| | - MO Karlsson
- Department of Pharmaceutical Biosciences; Uppsala University; Uppsala Sweden
| | - M Kriek
- Center for Clinical Genetics; Leiden University Medical Center; Leiden The Netherlands
| | | | - GP Patrinos
- University of Patras, School of Health Sciences, Department of Pharmacy; University Campus; Rion Patras Greece
| | - M Pirmohamed
- Department of Molecular and Clinical Pharmacology; Royal Liverpool University Hospital and University of Liverpool; Liverpool United Kingdom
| | - M Samwald
- Center for Medical Statistics, Informatics, and Intelligent Systems; Medical University of Vienna; Vienna Austria
| | - E Schaeffeler
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart; Germany and University of Tübingen; Tübingen Germany
| | - M Schwab
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart; Germany and University of Tübingen; Tübingen Germany
- Department of Clinical Pharmacology; University Hospital Tübingen; Tübingen Germany
- Department of Pharmacy and Biochemistry; University of Tübingen; Tübingen Germany
| | - D Steinberger
- Bio.logis Center for Human Genetics; Frankfurt am Main Germany
| | - J Stingl
- Research Division; Federal Institute for Drugs and Medical Devices; Bonn Germany
| | - G Sunder-Plassmann
- Division of Nephrology and Dialysis, Department of Internal Medicine III; Medical University of Vienna; Vienna Austria
| | - G Toffoli
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico; National Cancer Institute; Aviano Italy
| | - RM Turner
- Department of Molecular and Clinical Pharmacology; Royal Liverpool University Hospital and University of Liverpool; Liverpool United Kingdom
| | - MH van Rhenen
- Royal Dutch Pharmacists Association (KNMP); The Hague The Netherlands
| | - JJ Swen
- Department of Clinical Pharmacy and Toxicology; Leiden University Medical Center; Leiden The Netherlands
| | - H-J Guchelaar
- Department of Clinical Pharmacy and Toxicology; Leiden University Medical Center; Leiden The Netherlands
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15
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Rosenman MB, Decker B, Levy KD, Holmes AM, Pratt VM, Eadon MT. Lessons Learned When Introducing Pharmacogenomic Panel Testing into Clinical Practice. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2017; 20:54-59. [PMID: 28212969 PMCID: PMC7543044 DOI: 10.1016/j.jval.2016.08.727] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Accepted: 08/14/2016] [Indexed: 05/21/2023]
Abstract
OBJECTIVES Implementing new programs to support precision medicine in clinical settings is a complex endeavor. We describe challenges and potential solutions based on the Indiana GENomics Implementation: an Opportunity for the Underserved (INGenious) program at Eskenazi Health-one of six sites supported by the Implementing GeNomics In pracTicE network grant of the National Institutes of Health/National Human Genome Research Institute. INGenious is an implementation of a panel of genomic tests. METHODS We conducted a descriptive case study of the implementation of this pharmacogenomics program, which has a wide scope (14 genes, 27 medications) and a diverse population (patients who often have multiple chronic illnesses, in a large urban safety-net hospital and its outpatient clinics). CHALLENGES We placed the clinical pharmacogenomics implementation challenges into six categories: patient education and engagement in care decision making; clinician education and changes in standards of care; integration of technology into electronic health record systems; translational and implementation sciences in real-world clinical environments; regulatory and reimbursement considerations, and challenges in measuring outcomes. A cross-cutting theme was the need for careful attention to workflow. Our clinical setting, a safety-net health care system, presented some distinctive challenges. Patients often had multiple chronic illnesses and sometimes were taking more than one pharmacogenomics-relevant medication. Reaching patients for recruitment or follow-up was another challenge. CONCLUSIONS New, large-scale endeavors in health care are challenging. A description of the challenges that we encountered and the approaches that we adopted to address them may provide insights for those who implement and study innovations in other health care systems.
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Affiliation(s)
- Marc B Rosenman
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| | - Brian Decker
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kenneth D Levy
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ann M Holmes
- Department of Health Policy and Management, Richard M. Fairbanks School of Public Health, IUPUI, Indianapolis, IN, USA
| | - Victoria M Pratt
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
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16
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Finkelstein J, Friedman C, Hripcsak G, Cabrera M. Pharmacogenetic polymorphism as an independent risk factor for frequent hospitalizations in older adults with polypharmacy: a pilot study. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2016; 9:107-116. [PMID: 27789970 PMCID: PMC5072537 DOI: 10.2147/pgpm.s117014] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Pharmacogenetic testing identifies genetic biomarkers that are predictive of individual sensitivity to particular drugs. A significant proportion of medications that are widely prescribed for older adults are metabolized by enzymes that are encoded by highly polymorphic genes. Pharmacogenetic testing is increasingly used to optimize the medication regimen; however, its potential in older adults with polypharmacy has not been systematically explored. Following the initial case-series study, this study hypothesized that frequently hospitalized older adults with polypharmacy have higher frequency of pharmacogenetic polymorphism as compared to older adults with polypharmacy who are rarely admitted to a hospital. To test this hypothesis, a nested case-control study was conducted with pharmacogenetic polymorphism as an exposure and hospitalization rate as an outcome. In this study, frequently hospitalized older adults (≥65 years of age) with polypharmacy were matched with rarely hospitalized older adults with poly-pharmacy by age, gender, race, ethnicity, and chronic disease score. Average age and number of prescription drugs did not differ in cases and controls (77.2±5.0 and 78.3±5.1 years, 14.3±5.3 and 14.0±2.9 medications, respectively). No statistically significant difference in sociodemographic, clinical, and behavioral characteristics that are known to affect hospitalization risk was found between the cases and controls. Major pharmacogenetic polymorphism defined as presence of at least one allelic combination resulting in poor or rapid metabolizer status was identified in all the cases. No major pharmacogenetic polymorphisms were detected in controls. Based on the exact McNemar's test, the difference in major pharmacogenetic polymorphism frequency between cases and controls was statistically significant (p<0.05). In 50% of cases, more than one major pharmacogenetic polymorphism was found. The frequency of CYP2C19 rapid metabolizer, CYP3A4/5 poor metabolizer, VKORC1 low sensitivity, and CYP2D6 rapid metabolizer status in cases was 67%, 33%, 33%, and 17%, respectively, which significantly exceeded respective prevalence in general population. The mean number of major gene-drug interactions found in cases was 2.8±2.2, whereas no major drug-gene interactions were identified in controls. The difference in the number of major drug-gene interactions between cases and controls was statistically significant (p<0.05). The pilot data supported the hypothesis that pharmacogenetic polymorphism may represent an independent risk factor for frequent hospitalizations in older adults with polypharmacy. Due to small sample size, the results of this proof-of-concept study cannot be conclusive. Further work on the utility of pharmacogenetic testing for optimization of medication regimens in this vulnerable group of older adults is warranted.
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Affiliation(s)
| | | | | | - Manuel Cabrera
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, NY, USA
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17
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Haga SB, Mills R, Moaddeb J, Allen Lapointe N, Cho A, Ginsburg GS. Patient experiences with pharmacogenetic testing in a primary care setting. Pharmacogenomics 2016; 17:1629-1636. [PMID: 27648637 DOI: 10.2217/pgs-2016-0077] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
AIM To investigate patient experiences with pharmacogenetic (PGx) testing. METHODS Patients were offered PGx testing through a study on pharmacist-assisted delivery of PGx testing and invited to complete pre- and post-testing surveys about their experience. RESULTS Of 63 patients tested, 17 completed the baseline survey (27%). Interest in testing was mostly impacted by desire to inform selection of best treatment (n = 13). Seven of 12 patients that completed the follow-up survey indicated that their provider discussed the test result with them. Five patients understood their test result very or somewhat well. All would be likely to have PGx testing again. CONCLUSION Patients perceived PGx testing to be useful, though more effort may be needed to improve patient-provider communication of test results.
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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
| | - Rachel Mills
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, 304 Research Drive, Durham, NC 27708, USA
| | - Jivan Moaddeb
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, 304 Research Drive, Durham, NC 27708, USA
| | | | - Alex Cho
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, 304 Research Drive, Durham, NC 27708, USA
| | - Geoffrey S Ginsburg
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, 304 Research Drive, Durham, NC 27708, USA
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18
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Affiliation(s)
- Susanne B Haga
- Department of Medicine, Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, 304 Research Drive, Box 90141, Durham, NC 27708, USA
| | - Benjamin D Solomon
- Division of Medical Genomics, Inova Translational Medicine Institute, Associate Professor, Virginia Commonwealth University School of Medicine, 3300 Gallows Road, 2nd Floor, Claude Moore Building, Falls Church, VA 22042, USA
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