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Wixson RL, Dunnenberger HM, Dickerson DM, Tauchen AJ, Heshmat CM, Koh JL. Pain and Opioid use Following Total Knee Arthroplasty: Psycho-Social Factors are More Predictive Than Pharmacogenomics. J Arthroplasty 2024; 39:1214-1219. [PMID: 38081553 DOI: 10.1016/j.arth.2023.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 12/05/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024] Open
Abstract
BACKGROUND This prospective, observational study was designed to assess the phenotype variation of the genes associated with pain and opioid use following total knee arthroplasty (TKA) in comparison to psycho-social elements. METHODS Preoperative demographic data and Patient-Reported Outcomes Measurement Information System-43 scores were obtained on 305 elective TKA patients. Patient visual analog scale pain scores and opioid use were extracted from the hospital record. Following discharge, participants completed a daily log of visual analog scale pain score, and medications used over 30 days. Pharmacogenomic testing was performed for three genes, CYP2D6, COMT, and OPRM1, which are involved in the opioid pathway and pain modulation. RESULTS Other than increased pain seen in the COMT high activity group while in the hospital, none of the phenotype variations of the three genes were significantly associated with the participants' pain or opioid use. The Patient-Reported Outcomes Measurement Information System-43 domains of pain interference and anxiety were significantly associated with pain and opioid use using multiple logistic regression. CONCLUSIONS Pharmacogenomic testing in this study was not predictive of pain and opioid use following TKA compared with psycho-social variables.
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Affiliation(s)
- Richard L Wixson
- NorthShore Orthopaedic and Spine Institute, NorthShore University Health System, Skokie, Illinois
| | - Henry M Dunnenberger
- Mark R Neaman Center for Personalized Medicine, NorthShore University Health System, Evanston, Illinois
| | - David M Dickerson
- NorthShore Orthopaedic and Spine Institute, NorthShore University Health System, Skokie, Illinois
| | | | - Claire M Heshmat
- Biostatistics Division, Research Institute, NorthShore University Health System, Evanston, Illinois
| | - Jason L Koh
- NorthShore Orthopaedic and Spine Institute, NorthShore University Health System, Skokie, Illinois
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2
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Billings LK, Shi Z, Wei J, Rifkin AS, Zheng SL, Helfand BT, Ilbawi N, Dunnenberger HM, Hulick PJ, Qamar A, Xu J. Utility of Polygenic Scores for Differentiating Diabetes Diagnosis Among Patients With Atypical Phenotypes of Diabetes. J Clin Endocrinol Metab 2023; 109:107-113. [PMID: 37560999 DOI: 10.1210/clinem/dgad456] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/10/2023] [Accepted: 08/08/2023] [Indexed: 08/11/2023]
Abstract
CONTEXT Misclassification of diabetes type occurs in people with atypical presentations of type 1 diabetes (T1D) or type 2 diabetes (T2D). Although current clinical guidelines suggest clinical variables and treatment response as ways to help differentiate diabetes type, they remain insufficient for people with atypical presentations. OBJECTIVE This work aimed to assess the clinical utility of 2 polygenic scores (PGSs) in differentiating between T1D and T2D. METHODS Patients diagnosed with diabetes in the UK Biobank were studied (N = 41 787), including 464 (1%) and 15 923 (38%) who met the criteria for classic T1D and T2D, respectively, and 25 400 (61%) atypical diabetes. The validity of 2 published PGSs for T1D (PGST1D) and T2D (PGST2D) in differentiating classic T1D or T2D was assessed using C statistic. The utility of genetic probability for T1D based on PGSs (GenProb-T1D) was evaluated in atypical diabetes patients. RESULTS The joint performance of PGST1D and PGST2D for differentiating classic T1D or T2D was outstanding (C statistic = 0.91), significantly higher than that of PGST1D alone (0.88) and PGST2D alone (0.70), both P less than .001. Using an optimal cutoff of GenProb-T1D, 23% of patients with atypical diabetes had a higher probability of T1D and its validity was independently supported by clinical presentations that are characteristic of T1D. CONCLUSION PGST1D and PGST2D can be used to discriminate classic T1D and T2D and have potential clinical utility for differentiating these 2 types of diseases among patients with atypical diabetes.
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Affiliation(s)
- Liana K Billings
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA
| | - Zhuqing Shi
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Jun Wei
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Andrew S Rifkin
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - S Lilly Zheng
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Brian T Helfand
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Surgery, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Nadim Ilbawi
- Department of Family Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Henry M Dunnenberger
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Peter J Hulick
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Arman Qamar
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Jianfeng Xu
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL 60201, USA
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3
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Turner AJ, Nofziger C, Ramey BE, Ly RC, Bousman CA, Agúndez JAG, Sangkuhl K, Whirl-Carrillo M, Vanoni S, Dunnenberger HM, Ruano G, Kennedy MA, Phillips MS, Hachad H, Klein TE, Moyer AM, Gaedigk A. PharmVar Tutorial on CYP2D6 Structural Variation Testing and Recommendations on Reporting. Clin Pharmacol Ther 2023; 114:1220-1237. [PMID: 37669183 PMCID: PMC10840842 DOI: 10.1002/cpt.3044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 08/23/2023] [Indexed: 09/07/2023]
Abstract
The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus and a comprehensive summary of structural variation. CYP2D6 contributes to the metabolism of numerous drugs and, thus, genetic variation in its gene impacts drug efficacy and safety. To accurately predict a patient's CYP2D6 phenotype, testing must include structural variants including gene deletions, duplications, hybrid genes, and combinations thereof. This tutorial offers a comprehensive overview of CYP2D6 structural variation, terms, and definitions, a review of methods suitable for their detection and characterization, and practical examples to address the lack of standards to describe CYP2D6 structural variants or any other pharmacogene. This PharmVar tutorial offers practical guidance on how to detect the many, often complex, structural variants, as well as recommends terms and definitions for clinical and research reporting. Uniform reporting is not only essential for electronic health record-keeping but also for accurate translation of a patient's genotype into phenotype which is typically utilized to guide drug therapy.
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Affiliation(s)
- Amy J Turner
- Department of Pediatrics, Children’s Research Institute, The Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- RPRD Diagnostics LLC, Wauwatosa, Wisconsin, USA
| | | | | | - Reynold C Ly
- Department of Medical and Molecular Genetics, Division of Diagnostic Genomics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Chad A Bousman
- Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada
| | - José AG Agúndez
- University of Extremadura, Cáceres, Spain
- Institute of Molecular Pathology Biomarkers, Cáceres, Spain
| | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | | | | | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University Health System, Evanston, Illinois, USA
| | - Gualberto Ruano
- Institute of Living, Hartford Hospital (Hartford CT) and Department of Psychiatry, University of Connecticut School of Medicine (Farmington CT), USA
| | - Martin A Kennedy
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | | | - Houda Hachad
- Houda Hachad, Department of Clinical Operations, AccessDx Laboratories, Houston, Texas, USA
| | - Teri E Klein
- Departments of Biomedical Data Science and Medicine (BMIR), Stanford University, Stanford, California, USA
| | - Ann M Moyer
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Andrea Gaedigk
- Children’s Mercy Research Institute (CMRI), Kansas City, Missouri, USA
- School of Medicine, University of Missouri-Kansas City, Kansas City, Missouri, USA
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4
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David SP, Dunnenberger HM, Choi S, DePersia A, Ilbawi N, Ward C, Wake DT, Khandekar JD, Shannon Y, Hughes K, Miller N, Mangold KA, Sabatini LM, Helseth DL, Xu J, Sanders A, Kaul KL, Hulick PJ. Personalized medicine in a community health system: the NorthShore experience. Front Genet 2023; 14:1308738. [PMID: 38090148 PMCID: PMC10713750 DOI: 10.3389/fgene.2023.1308738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 11/06/2023] [Indexed: 02/01/2024] Open
Abstract
Genomic and personalized medicine implementation efforts have largely centered on specialty care in tertiary health systems. There are few examples of fully integrated care systems that span the healthcare continuum. In 2014, NorthShore University HealthSystem launched the Center for Personalized Medicine to catalyze the delivery of personalized medicine. Successful implementation required the development of a scalable family history collection tool, the Genetic and Wellness Assessment (GWA) and Breast Health Assessment (BHA) tools; integrated pharmacogenomics programming; educational programming; electronic medical record integration; and robust clinical decision support tools. To date, more than 225,000 patients have been screened for increased hereditary conditions, such as cancer risk, through these tools in primary care. More than 35,000 patients completed clinical genetic testing following GWA or BHA completion. An innovative program trained more than 100 primary care providers in genomic medicine, activated with clinical decision support and access to patient genetic counseling services and digital healthcare tools. The development of a novel bioinformatics platform (FLYPE) enabled the incorporation of genomics data into electronic medical records. To date, over 4,000 patients have been identified to have a pathogenic or likely pathogenic variant in a gene with medical management implications. Over 33,000 patients have clinical pharmacogenomics data incorporated into the electronic health record supported by clinical decision support tools. This manuscript describes the evolution, strategy, and successful multispecialty partnerships aligned with health system leadership that enabled the implementation of a comprehensive personalized medicine program with measurable patient outcomes through a genomics-enabled learning health system model that utilizes implementation science frameworks.
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Affiliation(s)
- Sean P. David
- Department of Family Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Family Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL, United States
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Outcomes Research Network, NorthShore University HealthSystem, Evanston, IL, United States
| | - Henry M. Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
| | - Sarah Choi
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
| | - Allison DePersia
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Outcomes Research Network, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL, United States
| | - Nadim Ilbawi
- Department of Family Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Family Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL, United States
| | - Christopher Ward
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
| | - Dyson T. Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
| | - Janardan D. Khandekar
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Kellogg Cancer Center, NorthShore University HealthSystem, Evanston, IL, United States
| | - Yvette Shannon
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL, United States
| | - Kristen Hughes
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
| | - Nicholas Miller
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
| | - Kathy A. Mangold
- Department of Pathology, University of Chicago Pritzker School of Medicine, Chicago, IL, United States
| | - Linda M. Sabatini
- Department of Pathology, University of Chicago Pritzker School of Medicine, Chicago, IL, United States
| | - Donald L. Helseth
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
| | - Jianfeng Xu
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
| | - Alan Sanders
- Center for Psychiatric Genetics, Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem, Evanston, IL, United States
- Departments of Psychiatry and Behavioral Neuroscience, University of Chicago Pritzker School of Medicine, Chicago, IL, United States
| | - Karen L. Kaul
- Outcomes Research Network, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Pathology, University of Chicago Pritzker School of Medicine, Chicago, IL, United States
- Department of Pathology, NorthShore University HealthSystem, Evanston, IL, United States
| | - Peter J. Hulick
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Outcomes Research Network, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL, United States
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5
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Shi Z, Wei J, Rifkin AS, Wang CH, Billings LK, Woo JSH, Talamonti MS, Vogel TJ, Moore E, Brockstein BE, Khandekar JD, Dunnenberger HM, Hulick PJ, Duggan D, Zheng SL, Lee CJ, Helfand BT, Tafur AJ, Xu J. Cancer-associated thrombosis by cancer sites and inherited factors in a prospective population-based cohort. Thromb Res 2023; 229:69-72. [PMID: 37419004 DOI: 10.1016/j.thromres.2023.06.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/23/2023] [Accepted: 06/23/2023] [Indexed: 07/09/2023]
Abstract
Cancer-associated thrombosis (CAT) is common and associated with mortality. We estimated CAT rate by cancer sites and inherited factors among cancer patients from the UK Biobank (N =70,406). The 12-month CAT rate after cancer diagnosis was 2.37% overall but varied considerably among cancer sites. Among the 10 cancer sites classified as 'high-risk' of CAT by the National Comprehensive Cancer Network guidelines, 6 had CAT rate <5%. In contrast, 5 cancer sites classified as 'average-risk' by the guidelines had CAT rate >5%. For inherited risk factors, both known mutation carriers in two genes (F5/F2) and polygenic score for venous thromboembolism (VTE) (PGSVTE) were independently associated with increased CAT risk. While F5/F2 identified 6% patients with high genetic-risk for CAT, adding PGSVTE identified 13 % patients at equivalent/higher genetic-risk to CAT than that of F5/F2 mutations. Findings from this large prospective study, if confirmed, provide critical data to update guidelines for CAT risk assessment.
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Affiliation(s)
- Zhuqing Shi
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA
| | - Jun Wei
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA
| | - Andrew S Rifkin
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA
| | - Chi-Hsiung Wang
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA
| | - Liana K Billings
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL, USA; University of Chicago Pritzker School of Medicine, Chicago, IL, USA
| | - Jonathan S H Woo
- Division of Hospital Medicine, NorthShore University HealthSystem, Evanston, IL, USA
| | - Mark S Talamonti
- Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA
| | | | - Elena Moore
- Kellogg Cancer Center, NorthShore University HealthSystem, Evanston, IL, USA
| | - Bruce E Brockstein
- Kellogg Cancer Center, NorthShore University HealthSystem, Evanston, IL, USA
| | - Janardan D Khandekar
- Kellogg Cancer Center, NorthShore University HealthSystem, Evanston, IL, USA; Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, USA
| | - Henry M Dunnenberger
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, USA
| | - Peter J Hulick
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL, USA; Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, USA
| | - David Duggan
- Affiliate of City of Hope, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - S Lilly Zheng
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA
| | - Cheong Jun Lee
- Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA
| | - Brian T Helfand
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA; University of Chicago Pritzker School of Medicine, Chicago, IL, USA; Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA
| | - Alfonso J Tafur
- Cardiovascular Institute, NorthShore University HealthSystem, Evanston, IL, USA.
| | - Jianfeng Xu
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA; University of Chicago Pritzker School of Medicine, Chicago, IL, USA; Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA; Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL, USA.
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6
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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: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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7
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Socco S, Wake DT, Lee JC, Dunnenberger HM. Pharmacogenomics of medications given via nonconventional administration routes: a scoping review. Pharmacogenomics 2022; 23:933-948. [DOI: 10.2217/pgs-2022-0093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Pharmacogenomics (PGx) implementation has become increasingly widespread. One of the most important aspects of this implementation process is the development of appropriate clinical decision support (CDS). Major PGx resources, such as the Clinical Pharmacogenetics Implementation Consortium, provide valuable recommendations for the development of CDS for specific gene–drug pairs but do not specify whether the administration route of a drug is clinically relevant. It is also unknown if PGx alerts for nonorally and non-intravenously administered PGx-relevant medications should be suppressed to reduce alert fatigue. The purpose of this scoping review was to identify studies and their clinical, pharmacokinetic and pharmacodynamic outcomes to better determine if CDS alerts are relevant for nonorally and non-intravenously administered PGx-relevant medications. Although this scoping review identified multiple PGx studies, the results of these studies were inconsistent, and more evidence is needed regarding different routes of medication administration and PGx.
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Affiliation(s)
- Samantha Socco
- Department of Pharmacy Practice, University of Illinois Chicago College of Pharmacy, Chicago, IL 60612, USA
- Department of Precision Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Dyson T Wake
- Department of Precision Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - James C Lee
- Department of Pharmacy Practice, University of Illinois Chicago College of Pharmacy, Chicago, IL 60612, USA
| | - Henry M Dunnenberger
- Department of Precision Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
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8
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Ho TT, Bell G, Gammal RS, Gregornik D, Wake DT, Dunnenberger HM. A clinician’s guide for counseling patients on results of a multigene pharmacogenomic panel. Am J Health Syst Pharm 2022; 79:1634-1644. [DOI: 10.1093/ajhp/zxac189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Disclaimer
In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.
Purpose
This article explores approaches to pharmacogenomic counseling for patients who have undergone multigene panel testing by describing the collective experience of 5 institutions.
Summary
Multigene panel pharmacogenomic testing has the potential to unlock a myriad of information about a patient’s past, present, and future drug response. The multifaceted nature of drug response coupled with the complexity of genetic results necessitates some form of patient education through pharmacogenomic counseling. Published literature regarding disclosure of pharmacogenomic test results is limited. This article compares the counseling practices of pharmacists from 5 different institutions with pharmacogenomics clinics whose experience represents perspectives ranging from academia to community clinical environments. Overarching counseling themes discussed during result disclosure center around (1) pharmacogenomic results, (2) gene-drug interactions, (3) gene-drug-drug interactions, (4) drug changes (5) future, familial, or disease-risk implications, (6) updates in the interpretation and application of pharmacogenomic results, (7) gauging patient comprehension, and (8) sharing results and supplemental information.
Conclusion
Dedicating time to counseling patients on the results of a multigene pharmacogenomic panel is important given the lifelong applications of a test that is generally performed only once. The content and methods of disclosing test results shared by the experiences of pharmacists at 5 different institutions serve as guide to be further refined as research addresses effective communication strategies that enhance patient comprehension of pharmacogenomic results.
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Affiliation(s)
- Teresa T Ho
- Department of Pharmacotherapeutics & Clinical Research, University of South Florida Taneja College of Pharmacy, Tampa , FL, and Department of Internal Medicine, University of South Florida Morsani College of Medicine, Tampa, FL, USA
| | - Gillian Bell
- Genetics & Personalized Medicine Department, Mission Health, Asheville, NC, and Genome Medical, South San Francisco , CA, USA
| | | | - David Gregornik
- Department of Pharmacy Practice, Massachusetts College of Pharmacy and Health Sciences, Boston , MA, USA
| | - Dyson T Wake
- Pharmacogenomics Program, Children's Minnesota, Minneapolis , MN, USA
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9
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David SP, Singh L, Pruitt J, Hensing A, Hulick P, Meltzer DO, O’Donnell PH, Dunnenberger HM. The Contribution of Pharmacogenetic Drug Interactions to 90-Day Hospital Readmissions: Preliminary Results from a Real-World Healthcare System. J Pers Med 2021; 11:jpm11121242. [PMID: 34945714 PMCID: PMC8705172 DOI: 10.3390/jpm11121242] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 11/21/2021] [Accepted: 11/21/2021] [Indexed: 01/09/2023] Open
Abstract
Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines exist for many medications commonly prescribed prior to hospital discharge, yet there are limited data regarding the contribution of gene-x-drug interactions to hospital readmissions. The present study evaluated the relationship between prescription of CPIC medications prescribed within 30 days of hospital admission and 90-day hospital readmission from 2010 to 2020 in a study population (N = 10,104) who underwent sequencing with a 14-gene pharmacogenetic panel. The presence of at least one pharmacogenetic indicator for a medication prescribed within 30 days of hospital admission was considered a gene-x-drug interaction. Multivariable logistic regression analyzed the association between one or more gene-x-drug interactions with 90-day readmission. There were 2211/2354 (93.9%) admitted patients who were prescribed at least one CPIC medication. Univariate analyses indicated that the presence of at least one identified gene-x-drug interaction increased the risk of 90-day readmission by more than 40% (OR = 1.42, 95% confidence interval (CI) 1.09–1.84) (p = 0.01). A multivariable model adjusting for age, race, sex, employment status, body mass index, and medical conditions slightly attenuated the effect (OR = 1.32, 95% CI 1.02–1.73) (p = 0.04). Our results suggest that the presence of one or more CPIC gene-x-drug interactions increases the risk of 90-day hospital readmission, even after adjustment for demographic and clinical risk factors.
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Affiliation(s)
- Sean P. David
- Department of Family Medicine, NorthShore University Health System, Evanston, IL 60201, USA;
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA; (P.H.); (D.O.M.); (P.H.O.)
- Correspondence:
| | - Lavisha Singh
- Department of Statistics, NorthShore University Health System, Evanston, IL 60201, USA;
| | - Jaclyn Pruitt
- Department of Surgery, NorthShore University Health System, Evanston, IL 60201, USA;
- Outcomes Research Network, NorthShore University Health System, Evanston, IL 60201, USA;
| | - Andrew Hensing
- Outcomes Research Network, NorthShore University Health System, Evanston, IL 60201, USA;
| | - Peter Hulick
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA; (P.H.); (D.O.M.); (P.H.O.)
- Center for Personalized Medicine, NorthShore University Health System, Evanston, IL 60201, USA
| | - David O. Meltzer
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA; (P.H.); (D.O.M.); (P.H.O.)
| | - Peter H. O’Donnell
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA; (P.H.); (D.O.M.); (P.H.O.)
| | - Henry M. Dunnenberger
- Department of Family Medicine, NorthShore University Health System, Evanston, IL 60201, USA;
- Outcomes Research Network, NorthShore University Health System, Evanston, IL 60201, USA;
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10
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Mroz P, Michel S, Allen JD, Meyer T, McGonagle EJ, Carpentier R, Vecchia A, Schlichte A, Bishop JR, Dunnenberger HM, Yohe S, Thyagarajan B, Jacobson PA, Johnson SG. Development and Implementation of In-House Pharmacogenomic Testing Program at a Major Academic Health System. Front Genet 2021; 12:712602. [PMID: 34745204 PMCID: PMC8564018 DOI: 10.3389/fgene.2021.712602] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/16/2021] [Indexed: 12/26/2022] Open
Abstract
Pharmacogenomics (PGx) studies how a person's genes affect the response to medications and is quickly becoming a significant part of precision medicine. The clinical application of PGx principles has consistently been cited as a major opportunity for improving therapeutic outcomes. Several recent studies have demonstrated that most individuals (> 90%) harbor PGx variants that would be clinically actionable if prescribed a medication relevant to that gene. In multiple well-conducted studies, the results of PGx testing have been shown to guide therapy choice and dosing modifications which improve treatment efficacy and reduce the incidence of adverse drug reactions (ADRs). Although the value of PGx testing is evident, its successful implementation in a clinical setting presents a number of challenges to molecular diagnostic laboratories, healthcare systems, providers and patients. Different molecular methods can be applied to identify PGx variants and the design of the assay is therefore extremely important. Once the genotyping results are available the biggest technical challenge lies in turning this complex genetic information into phenotypes and actionable recommendations that a busy clinician can effectively utilize to provide better medical care, in a cost-effective, efficient and reliable manner. In this paper we describe a successful and highly collaborative implementation of the PGx testing program at the University of Minnesota and MHealth Fairview Molecular Diagnostic Laboratory and selected Pharmacies and Clinics. We offer detailed descriptions of the necessary components of the pharmacogenomic testing implementation, the development and technical validation of the in-house SNP based multiplex PCR based assay targeting 20 genes and 48 SNPs as well as a separate CYP2D6 copy number assay along with the process of PGx report design, results of the provider and pharmacists usability studies, and the development of the software tool for genotype-phenotype translation and gene-phenotype-drug CPIC-based recommendations. Finally, we outline the process of developing the clinical workflow that connects the providers with the PGx experts within the Molecular Diagnostic Laboratory and the Pharmacy.
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Affiliation(s)
- Pawel Mroz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Stephen Michel
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Josiah D Allen
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | - Tim Meyer
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States
| | - Erin J McGonagle
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | | | | | | | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States.,Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Henry M Dunnenberger
- Mark R Neaman Center for Personalized Medicine Center, NorthShore University HealthSystem, Evanston, IL, United States
| | - Sophia Yohe
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Pamala A Jacobson
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States
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11
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Wake DT, Smith DM, Kazi S, Dunnenberger HM. Pharmacogenomic Clinical Decision Support: A Review, How-to Guide, and Future Vision. Clin Pharmacol Ther 2021; 112:44-57. [PMID: 34365648 PMCID: PMC9291515 DOI: 10.1002/cpt.2387] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 07/28/2021] [Indexed: 02/06/2023]
Abstract
Clinical decision support (CDS) is an essential part of any pharmacogenomics (PGx) implementation. Increasingly, institutions have implemented CDS tools in the clinical setting to bring PGx data into patient care, and several have published their experiences with these implementations. However, barriers remain that limit the ability of some programs to create CDS tools to fit their PGx needs. Therefore, the purpose of this review is to summarize the types, functions, and limitations of PGx CDS currently in practice. Then, we provide an approachable step‐by‐step how‐to guide with a case example to help implementers bring PGx to the front lines of care regardless of their setting. Particular focus is paid to the five “rights” of CDS as a core around designing PGx CDS tools. Finally, we conclude with a discussion of opportunities and areas of growth for PGx CDS.
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Affiliation(s)
- Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - D Max Smith
- MedStar Health, Columbia, Maryland, USA.,Georgetown University Medical Center, Washington, DC, USA
| | - Sadaf Kazi
- Georgetown University Medical Center, Washington, DC, USA.,National Center for Human Factors in Healthcare, MedStar Health Research Institute Washington, Washington, DC, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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12
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Lemke AA, Amendola LM, Thompson J, Dunnenberger HM, Kuchta K, Wang C, Dilzell-Yu K, Hulick PJ. Patient-Reported Outcomes and Experiences with Population Genetic Testing Offered Through a Primary Care Network. Genet Test Mol Biomarkers 2021; 25:152-160. [PMID: 33596141 PMCID: PMC7891215 DOI: 10.1089/gtmb.2020.0275] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Aims: To explore patient experiences in a large-scale primary care-based, preemptive genetic testing program. Methods: Patients who received genetic results from the initiative were invited to participate in an online survey 3 weeks postresult disclosure. A 6-month follow-up survey was sent to assess changes over time. Results: The initial survey was completed by 1646 patients, with 544 completing the 6-month follow-up survey. The following outcomes were high overall: patient-reported understanding of results (cancer: 87%; cardiac: 86%); perceived utility (75%); positive emotions (relieved: 66.8%; happy: 62.0%); family result sharing (67.6%); and satisfaction (87%), although analysis by demographic factors identified groups who may benefit from additional education and emotional support. Results-related health behaviors and discussions with providers increased over time (screening procedures 6.1% to 14.2% p < 0.001; provider discussion 10.3% to 25.3%, p < 0.001), and were more likely to take place for patients with positive cancer and/or cardiac results (39.8% vs. 7.6%, p < 0.001). Forty-seven percent of patients reported insurance discrimination concerns, and most (79.4%) were not familiar with privacy and nondiscrimination laws. Concerns regarding discrimination and negative emotions decreased between the two survey time points (privacy issues 44.6% to 35.1% p < 0.001; life insurance discrimination concerns 35.5% to 29.6%, p = 0.001; anxiety 8.1% to 3.3%, p < 0.001; and uncertainty 19.8% to 12.8%, p < 0.001). These findings led to the development and integration of additional patient resources to improve program implementation. Conclusion: Our findings highlight patient experiences with and areas of need in a community-based genomic screening pilot initiative using a mixed primary care/genetics provider model to deliver precision medicine.
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Affiliation(s)
- Amy A Lemke
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Laura M Amendola
- Division of Medical Genetics, University of Washington, Seattle, Washington, USA
| | - Jennifer Thompson
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Henry M Dunnenberger
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Kristine Kuchta
- Center for Biomedical Research Informatics, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Chi Wang
- Center for Biomedical Research Informatics, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Kristen Dilzell-Yu
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Peter J Hulick
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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13
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Luzum JA, Petry N, Taylor AK, Van Driest SL, Dunnenberger HM, Cavallari LH. Moving Pharmacogenetics Into Practice: It's All About the Evidence! Clin Pharmacol Ther 2021; 110:649-661. [PMID: 34101169 DOI: 10.1002/cpt.2327] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 05/27/2021] [Indexed: 12/19/2022]
Abstract
The evidence for pharmacogenetics has grown rapidly in recent decades. However, the strength of evidence required for the clinical implementation of pharmacogenetics is highly debated. Therefore, the purpose of this review is to summarize different perspectives on the evidence required for the clinical implementation of pharmacogenetics. First, we present two patient cases that demonstrate how knowledge of pharmacogenetic evidence affected their care. Then we summarize resources that curate pharmacogenetic evidence, types of evidence (with an emphasis on randomized controlled trials [RCT]) and their limitations, and different perspectives from implementers, clinicians, and patients. We compare pharmacogenetics to a historical example (i.e., the evidence required for the clinical implementation of pharmacokinetics/therapeutic drug monitoring), and we provide future perspectives on the evidence for pharmacogenetic panels and the need for more education in addition to evidence. Although there are differences in the interpretation of pharmacogenetic evidence across resources, efforts for standardization are underway. Survey data illustrate the value of pharmacogenetic testing from the patient perspective, with their providers seen as key to ensuring maximum benefit from test results. However, clinicians and practice guidelines from medical societies often rely on RCT data to guide treatment decisions, which are not always feasible or ethical in pharmacogenetics. Thus, recognition of other types of evidence to support pharmacogenetic implementation is needed. Among pharmacogenetic implementers, consistent evidence of pharmacogenetic associations is deemed most critical. Ultimately, moving pharmacogenetics into practice will require consideration of multiple stakeholder perspectives, keeping particularly attuned to the voice of the ultimate stakeholder-the patient.
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Affiliation(s)
- Jasmine A Luzum
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA
| | - Natasha Petry
- Department of Pharmacy Practice, College of Health Professions, North Dakota State University, Fargo, North Dakota, USA.,Sanford Imagenetics, Sioux Falls, South Dakota, USA
| | - Annette K Taylor
- Colorado Coagulation, Laboratory Corporation of America Holdings, Englewood, Colorado, USA
| | - Sara L Van Driest
- Departments of Pediatrics and Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
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14
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Gammal RS, Smith DM, Wiisanen KW, Cusimano JM, Pettit RS, Stephens JW, Walko CM, Yang RH, Dunnenberger HM. The pharmacist's responsibility to ensure appropriate use of direct‐to‐consumer genetic testing. J Am Coll Clin Pharm 2021. [DOI: 10.1002/jac5.1437] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
| | - D. Max Smith
- American College of Clinical Pharmacy Lenexa Kansas USA
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15
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Crews KR, Monte AA, Huddart R, Caudle KE, Kharasch ED, Gaedigk A, Dunnenberger HM, Leeder JS, Callaghan JT, Samer CF, Klein TE, Haidar CE, Van Driest SL, Ruano G, Sangkuhl K, Cavallari LH, Müller DJ, Prows CA, Nagy M, Somogyi AA, Skaar TC. Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2D6, OPRM1, and COMT Genotypes and Select Opioid Therapy. Clin Pharmacol Ther 2021; 110:888-896. [PMID: 33387367 DOI: 10.1002/cpt.2149] [Citation(s) in RCA: 181] [Impact Index Per Article: 60.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 12/02/2020] [Indexed: 11/08/2022]
Abstract
Opioids are mainly used to treat both acute and chronic pain. Several opioids are metabolized to some extent by CYP2D6 (codeine, tramadol, hydrocodone, oxycodone, and methadone). Polymorphisms in CYP2D6 have been studied for an association with the clinical effect and safety of these drugs. Other genes that have been studied for their association with opioid clinical effect or adverse events include OPRM1 (mu receptor) and COMT (catechol-O-methyltransferase). This guideline updates and expands the 2014 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 genotype and codeine therapy and includes a summation of the evidence describing the impact of CYP2D6, OPRM1, and COMT on opioid analgesia and adverse events. We provide therapeutic recommendations for the use of CYP2D6 genotype results for prescribing codeine and tramadol and describe the limited and/or weak data for CYP2D6 and hydrocodone, oxycodone, and methadone, and for OPRM1 and COMT for clinical use.
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Affiliation(s)
- Kristine R Crews
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Andrew A Monte
- Department of Emergency Medicine & Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Rachel Huddart
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Kelly E Caudle
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Evan D Kharasch
- Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Andrea Gaedigk
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy Kansas City, Kanas City, Missouri, USA.,School of Medicine, University of Missouri-Kansas City, Kansas City, Missouri, USA
| | - Henry M Dunnenberger
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - J Steven Leeder
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy Kansas City, Kanas City, Missouri, USA.,School of Medicine, University of Missouri-Kansas City, Kansas City, Missouri, USA
| | - John T Callaghan
- Department of Medicine, Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Caroline Flora Samer
- Clinical Pharmacology and Toxicology Department, Geneva University Hospitals, Geneva, Switzerland
| | - Teri E Klein
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Cyrine E Haidar
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Sara L Van Driest
- Departments of Pediatrics and Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Gualberto Ruano
- Institute of Living Hartford Hospital, Genomas Lab of Personalized Health, University of Connecticut School of Medicine and University of Puerto Rico Medical Sciences, Hartford, Connecticut, USA
| | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Daniel J Müller
- Department of Psychiatry, Campbell Family Mental Health Research Institute of CAMH, University of Toronto, Toronto, Ontario, Canada
| | - Cynthia A Prows
- Divisions of Human Genetics and Patient Services, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Mohamed Nagy
- Department of Pharmaceutical Services, Children's Cancer Hospital Egypt 57357, Cairo, Egypt
| | - Andrew A Somogyi
- Discipline of Pharmacology, Adelaide Medical School, University of Adelaide, Adelaide, Australia
| | - Todd C Skaar
- Department of Medicine, Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, USA
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16
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Wake DT, Bell GC, Gregornik DB, Ho TT, Dunnenberger HM. Synthesis of major pharmacogenomics pretest counseling themes: a multisite comparison. Pharmacogenomics 2021; 22:165-176. [PMID: 33461326 DOI: 10.2217/pgs-2020-0168] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
The accessibility of pharmacogenomic (PGx) testing has grown substantially over the last decade and with it has arisen a demand for patients to be counseled on the use of these tests. While guidelines exist for the use of PGx results; objective determinants for who should receive PGx testing remain incomplete. PGx clinical services have been created to meet these screening and education needs and significant variability exists between these programs. This article describes the practices of four PGx clinics during pretest counseling sessions. A description of the major tenets of the benefits, limitations and risks of testing are compiled. Additional tools are provided to serve as a foundation for those wishing to begin or expand their own counseling service.
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Affiliation(s)
- Dyson T Wake
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Gillian C Bell
- Genetics & Personalized Medicine Department, Mission Health, Asheville, NC 28803, USA
| | - David B Gregornik
- Pharmacogenomics Program, Children's Minnesota, Minneapolis, MN 55404, USA
| | - Teresa T Ho
- Department of Pharmacotherapeutics & Clinical Research, University of South Florida Taneja College of Pharmacy, Tampa, FL 33612, USA
| | - Henry M Dunnenberger
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
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17
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Helseth DL, Gulukota K, Miller N, Yang M, Werth T, Sabatini LM, Bouma M, Dunnenberger HM, Wake DT, Hulick PJ, Kaul KL, Khandekar JD. Flype: Software for enabling personalized medicine. Am J Med Genet C Semin Med Genet 2020; 187:37-47. [PMID: 33270363 PMCID: PMC7984435 DOI: 10.1002/ajmg.c.31867] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 11/19/2020] [Accepted: 11/20/2020] [Indexed: 02/02/2023]
Abstract
The advent of next generation DNA sequencing (NGS) has revolutionized clinical medicine by enabling wide‐spread testing for genomic anomalies and polymorphisms. With that explosion in testing, however, come several informatics challenges including managing large amounts of data, interpreting the results and providing clinical decision support. We present Flype, a web‐based bioinformatics platform built by a small group of bioinformaticians working in a community hospital setting, to address these challenges by allowing us to: (a) securely accept data from a variety of sources, (b) send orders to a variety of destinations, (c) perform secondary analysis and annotation of NGS data, (d) provide a central repository for all genomic variants, (e) assist with tertiary analysis and clinical interpretation, (f) send signed out data to our EHR as both PDF and discrete data elements, (g) allow population frequency analysis and (h) update variant annotation when literature knowledge evolves. We discuss the multiple use cases Flype supports such as (a) in‐house NGS tests, (b) in‐house pharmacogenomics (PGX) tests, (c) dramatic scale‐up of genomic testing using an external lab, (d) consumer genomics using two external partners, and (e) a variety of reporting tools. The source code for Flype is available upon request to the authors.
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Affiliation(s)
- Donald L Helseth
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Kamalakar Gulukota
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Nicholas Miller
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Mathew Yang
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Tom Werth
- Health Information Technology, NorthShore University HealthSystem, Skokie, Illinois, USA
| | - Linda M Sabatini
- Department of Pathology, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Mike Bouma
- Department of Pathology, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Peter J Hulick
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA.,Center for Medical Genetics, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Karen L Kaul
- Department of Pathology, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Janaradan D Khandekar
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA.,Kellogg Cancer Center, NorthShore University HealthSystem, Evanston, Illinois, USA
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18
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Luvsantseren S, Whirl-Carrillo M, Sangkuhl K, Shin N, Wen A, Empey P, Alam B, David S, Dunnenberger HM, Orlando L, Altman R, Palaniappan L. Variant Interpretation in Current Pharmacogenetic Testing. J Pers Med 2020; 10:jpm10040204. [PMID: 33142667 PMCID: PMC7712137 DOI: 10.3390/jpm10040204] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 10/26/2020] [Accepted: 10/29/2020] [Indexed: 11/17/2022] Open
Abstract
In the current marketplace, there are now more than a dozen commercial companies providing pharmacogenetic tests. Each company varies in the panel of genes they test and the variants they are able to screen for. The reports generated by these companies provide phenotypic interpretations of pharmacogenes and clinically actionable gene–drug interactions based on internally curated data and proprietary algorithms. The freedom to choose the types of evidence to include versus exclude in interpreting genomics has created reporting discrepancies in the industry. The case report presented here reveals the discordant phenotype analysis provided by two pharmacogenetic testing companies. The uncertainty and unnecessary distress experienced by the patient highlights the need for consensus in phenotype reporting within the industry.
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Affiliation(s)
- Sally Luvsantseren
- Department of Pharmacy, Stanford Health Care, Stanford, CA 94305, USA; (S.L.); (N.S.); (A.W.)
| | - Michelle Whirl-Carrillo
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; (M.W.-C.); (K.S.); (R.A.)
| | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; (M.W.-C.); (K.S.); (R.A.)
| | - Nancy Shin
- Department of Pharmacy, Stanford Health Care, Stanford, CA 94305, USA; (S.L.); (N.S.); (A.W.)
| | - Alice Wen
- Department of Pharmacy, Stanford Health Care, Stanford, CA 94305, USA; (S.L.); (N.S.); (A.W.)
| | - Philip Empey
- Department of Pharmacy and Therapeutics, Center for Clinical Pharmaceutical Sciences, University of Pittsburgh School of Pharmacy, Pittsburgh, PA 15261, USA;
| | - Benish Alam
- Department of Pharmacotherapy & Translational Research, University of Florida College of Pharmacy, Gainesville, FL 32610, USA;
| | - Sean David
- Department of Family Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA;
| | - Henry M. Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University Health System, Evanston, IL 60201, USA;
| | - Lori Orlando
- Department of Medicine and The Center for Applied Genomics and Precision Medicine, Duke University, Durham, NC 27708, USA;
| | - Russ Altman
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; (M.W.-C.); (K.S.); (R.A.)
| | - Latha Palaniappan
- Division of Primary Care and Population Health, School of Medicine, Stanford University, Stanford, CA 94305, USA
- Correspondence:
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19
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Lemke AA, Amendola LM, Kuchta K, Dunnenberger HM, Thompson J, Johnson C, Ilbawi N, Oshman L, Hulick PJ. Primary Care Physician Experiences with Integrated Population-Scale Genetic Testing: A Mixed-Methods Assessment. J Pers Med 2020; 10:E165. [PMID: 33066060 PMCID: PMC7720124 DOI: 10.3390/jpm10040165] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 10/05/2020] [Accepted: 10/06/2020] [Indexed: 12/19/2022] Open
Abstract
The scalable delivery of genomic medicine requires collaboration between genetics and non-genetics providers. Thus, it is essential to investigate and address the perceived value of and barriers to incorporating genetic testing into the clinical practice of primary care providers (PCPs). We used a mixed-methods approach of qualitative interviews and surveys to explore the experience of PCPs involved in the pilot DNA-10K population genetic testing program. Similar to previous research, PCPs reported low confidence with tasks related to ordering, interpreting and managing the results of genetic tests, and identified the need for additional education. PCPs endorsed high levels of utility for patients and their families but noted logistical challenges to incorporating genetic testing into their practice. Overall PCPs were not familiar with the United States' Genetic Information Nondiscrimination Act and they expressed high levels of concern for patient data privacy and potential insurance discrimination. This PCP feedback led to the development and implementation of several processes to improve the PCP experience with the DNA-10K program. These results contribute to the knowledge base regarding genomic implementation using a mixed provider model and may be beneficial for institutions developing similar clinical programs.
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Affiliation(s)
- Amy A. Lemke
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA; (H.M.D.); (J.T.); (C.J.); (P.J.H.)
| | - Laura M. Amendola
- Division of Medical Genetics, University of Washington, Seattle, WA 98115, USA;
| | - Kristine Kuchta
- Center for Biomedical Research Informatics, NorthShore University HealthSystem, Evanston, IL 60201, USA;
| | - Henry M. Dunnenberger
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA; (H.M.D.); (J.T.); (C.J.); (P.J.H.)
| | - Jennifer Thompson
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA; (H.M.D.); (J.T.); (C.J.); (P.J.H.)
| | - Christian Johnson
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA; (H.M.D.); (J.T.); (C.J.); (P.J.H.)
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Nadim Ilbawi
- Department of Family Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA; (N.I.); (L.O.)
| | - Lauren Oshman
- Department of Family Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA; (N.I.); (L.O.)
| | - Peter J. Hulick
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA; (H.M.D.); (J.T.); (C.J.); (P.J.H.)
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20
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Nofziger C, Turner AJ, Sangkuhl K, Whirl-Carrillo M, Agúndez JAG, Black JL, Dunnenberger HM, Ruano G, Kennedy MA, Phillips MS, Hachad H, Klein TE, Gaedigk A. PharmVar GeneFocus: CYP2D6. Clin Pharmacol Ther 2019; 107:154-170. [PMID: 31544239 DOI: 10.1002/cpt.1643] [Citation(s) in RCA: 133] [Impact Index Per Article: 26.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 08/29/2019] [Indexed: 01/13/2023]
Abstract
The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus. CYP2D6 genetic variation impacts the metabolism of numerous drugs and, thus, can impact drug efficacy and safety. This GeneFocus provides a comprehensive overview and summary of CYP2D6 genetic variation and describes how the information provided by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).
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Affiliation(s)
| | - Amy J Turner
- Section of Genomic Pediatrics, Department of Pediatrics, Children's Research Institute, The Medical College of Wisconsin, Milwaukee, Wisconsin, USA.,RPRD Diagnostics LLC, Wauwatosa, Wisconsin, USA
| | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | | | - José A G Agúndez
- University Institute of Molecular Pathology Biomarkers, UEx, Cáceres, Spain.,ARADyAL Instituto de Salud Carlos III, Madrid, Spain
| | - John L Black
- Division of Laboratory Genetics and Genomics, Personalized Genomics Laboratory, Mayo Clinic Laboratories, Mayo Clinic, Rochester, Minnesota, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanton, Illinois, USA
| | - Gualberto Ruano
- Institute of Living at Hartford Hospital, Genomas Laboratory of Personalized Health, Hartford, Connecticut, USA
| | - Martin A Kennedy
- Department of Pathology and Biomedical Science, University Otago, Christchurch, New Zealand
| | | | - Houda Hachad
- Translational Software, Bellevue, Washington, USA
| | - Teri E Klein
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Andrea Gaedigk
- Division of Clinical Pharmacology, Toxicology, & Therapeutic Innovation, Children's Mercy Kansas City, Kansas City, Missouri, USA.,School of Medicine, University of Missouri-Kansas City, Kansas City, Missouri, USA
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21
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Hicks JK, Aquilante CL, Dunnenberger HM, Gammal RS, Funk RS, Aitken SL, Bright DR, Coons JC, Dotson KM, Elder CT, Groff LT, Lee JC. Precision Pharmacotherapy: Integrating Pharmacogenomics into Clinical Pharmacy Practice. J Am Coll Clin Pharm 2019; 2:303-313. [PMID: 32984775 DOI: 10.1002/jac5.1118] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Precision pharmacotherapy encompasses the use of therapeutic drug monitoring; evaluation of liver and renal function, genomics, and environmental and lifestyle exposures; and analysis of other unique patient or disease characteristics to guide drug selection and dosing. This paper articulates real-world clinical applications of precision pharmacotherapy, focusing exclusively on the emerging field of clinical pharmacogenomics. This field is evolving rapidly, and clinical pharmacists now play an invaluable role in the clinical implementation, education, and research applications of pharmacogenomics. This paper provides an overview of the evolution of pharmacogenomics in clinical pharmacy practice, together with recommendations on how the American College of Clinical Pharmacy (ACCP) can support the advancement of clinical pharmacogenomics implementation, education, and research. Commonalities among successful clinical pharmacogenomics implementation and education programs are identified, with recommendations for how ACCP can leverage and advance these common themes. Opportunities are also provided to support the research needed to move the practice and application of pharmacogenomics forward.
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22
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23
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Arya R, Botton MR, Campos KC, Caudle KE, Cavallari LH, Drozda K, Duconge J, Duggirala R, Dunnenberger HM, Gammal RS, Jenkinson CP, Lam YWF, Lee EJD, Limenta M, Mallayasamy S, Mohamed EHM, Momary KM, Owusu Obeng A, Penzak SR, Samwald M, Scott ER, Scott SA, Someya T, Swen JJ, Tan-Koi WC, Vandell A, Wallsten RL, Yin O. List of Contributors. Pharmacogenomics 2019. [DOI: 10.1016/b978-0-12-812626-4.01002-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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24
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Abstract
Genomic medicine provides opportunities to personalize cancer therapy for an individual patient. Although novel targeted therapies prolong survival, most patients with cancer continue to suffer from burdensome symptoms including pain, depression, neuropathy, nausea and vomiting, and infections, which significantly impair quality of life. Suboptimal management of these symptoms can negatively affect response to cancer treatment and overall prognosis. The effect of genetic variation on drug response-otherwise known as pharmacogenomics-is well documented and directly influences an individual patient's response to antiemetics, opioids, neuromodulators, antidepressants, antifungals, and more. The growing body of pharmacogenomic data can now guide clinicians to select the safest and most effective supportive medications for an individual patient with cancer from the very first prescription. This review outlines a theoretical patient case and the implications of using pharmacogenetic test results to personalize supportive care throughout the cancer care continuum. IMPLICATIONS FOR PRACTICE Integration of palliative medicine into the cancer care continuum has resulted in increased quality of life and survival for patients with many cancer types. However, suboptimal management of symptoms such as pain, neuropathy, depression, and nausea and vomiting continues to place a heavy burden on patients with cancer. As demonstrated in this theoretical case, pharmacogenomics can have a major effect on clinical response to medications used to treat these conditions. Recognizing the value of supportive care pharmacogenomics in oncology and application into routine practice offers an objective choice for the safest and most effective treatment compared with the traditional trial and error method.
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Affiliation(s)
- Jai N Patel
- Levine Cancer Institute, Carolinas HealthCare System, Charlotte, North Carolina, USA
| | - Lauren A Wiebe
- NorthShore University Health System, Evanston, Illinois, USA
| | | | - Howard L McLeod
- The DeBartolo Family Personalized Medicine Institute, Moffitt Cancer Center, Tampa, Florida, USA
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25
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Lemke AA, Hulick PJ, Wake DT, Wang C, Sereika AW, Yu KD, Glaser NS, Dunnenberger HM. Patient perspectives following pharmacogenomics results disclosure in an integrated health system. Pharmacogenomics 2018; 19:321-331. [DOI: 10.2217/pgs-2017-0191] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Aim: To assess patient perceptions and utilization of pharmacogenomics (PGx) testing in an integrated community health system. Methods: Fifty-seven patients completed an online survey assessing their experiences with PGx testing offered through two methods: a designated PGx clinic or direct access in-home testing. Results: The majority of participants perceived PGx testing as helpful in their healthcare and reported understanding their results. Some had concerns about privacy and discrimination; most lacked familiarity with the Genetic Information Nondiscrimination Act. There were no significant differences in views between participants tested through either model. Conclusion: Participants reported value in both methods of PGx testing. Patient experiences, understanding and result utilization will play an important role in informing future development and implementation of PGx programs.
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Affiliation(s)
- Amy A Lemke
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Peter J Hulick
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Dyson T Wake
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Chi Wang
- Biostatistics & Research Informatics, NorthShore University HealthSystem, 1001 University Place, Suite 146, Evanston, IL 60201, USA
| | - Annette W Sereika
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Kristen Dilzell Yu
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Nicole S Glaser
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Henry M Dunnenberger
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
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26
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Phillips EJ, Sukasem C, Whirl-Carrillo M, Müller DJ, Dunnenberger HM, Chantratita W, Goldspiel B, Chen YT, Carleton BC, George AL, Mushiroda T, Klein T, Gammal RS, Pirmohamed M. Clinical Pharmacogenetics Implementation Consortium Guideline for HLA Genotype and Use of Carbamazepine and Oxcarbazepine: 2017 Update. Clin Pharmacol Ther 2018; 103:574-581. [PMID: 29392710 DOI: 10.1002/cpt.1004] [Citation(s) in RCA: 152] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 12/13/2017] [Accepted: 12/20/2017] [Indexed: 12/15/2022]
Abstract
The variant allele HLA-B*15:02 is strongly associated with greater risk of Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) in patients treated with carbamazepine or oxcarbazepine. The variant allele HLA-A*31:01 is associated with greater risk of maculopapular exanthema, drug reaction with eosinophilia and systemic symptoms, and SJS/TEN in patients treated with carbamazepine. We summarize evidence from the published literature supporting these associations and provide recommendations for carbamazepine and oxcarbazepine use based on HLA genotypes.
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Affiliation(s)
| | - Chonlaphat Sukasem
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.,Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center, Faculty of Medicine Ramathibodi Hospital, Bangkok, Thailand
| | | | - Daniel J Müller
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry and Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Henry M Dunnenberger
- Center for Molecular Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Wasun Chantratita
- Virology Laboratory, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.,Center for Medical Genomics, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Barry Goldspiel
- Pharmacy Department, National Institutes of Health Clinical Center, Bethesda, Maryland, USA
| | - Yuan-Tsong Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.,Department of Pediatrics, Duke University Medical Center, Durham, North Carolina, USA
| | - Bruce C Carleton
- Division of Translational Therapeutics, Department of Pediatrics, Faculty of Medicine, University of British Columbia, and BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada
| | - Alfred L George
- Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Taisei Mushiroda
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Science, Yokohama, Japan
| | - Teri Klein
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Roseann S Gammal
- Department of Pharmacy Practice, MCPHS University, Boston, Massachusetts, USA.,Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Munir Pirmohamed
- Department of Pharmacology, University of Liverpool, Liverpool, UK
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27
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Hicks JK, Dunnenberger HM, Gumpper KF, Haidar CE, Hoffman JM. Integrating pharmacogenomics into electronic health records with clinical decision support. Am J Health Syst Pharm 2018; 73:1967-1976. [PMID: 27864204 DOI: 10.2146/ajhp160030] [Citation(s) in RCA: 91] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
PURPOSE Existing pharmacogenomic informatics models, key implementation steps, and emerging resources to facilitate the development of pharmacogenomic clinical decision support (CDS) are described. SUMMARY Pharmacogenomics is an important component of precision medicine. Informatics, especially CDS in the electronic health record (EHR), is a critical tool for the integration of pharmacogenomics into routine patient care. Effective integration of pharmacogenomic CDS into the EHR can address implementation challenges, including the increasing volume of pharmacogenomic clinical knowledge, the enduring nature of pharmacogenomic test results, and the complexity of interpreting results. Both passive and active CDS provide point-of-care information to clinicians that can guide the systematic use of pharmacogenomics to proactively optimize pharmacotherapy. Key considerations for a successful implementation have been identified; these include clinical workflows, identification of alert triggers, and tools to guide interpretation of results. These considerations, along with emerging resources from the Clinical Pharmacogenetics Implementation Consortium and the National Academy of Medicine, are described. CONCLUSION The EHR with CDS is essential to curate pharmacogenomic data and disseminate patient-specific information at the point of care. As part of the successful implementation of pharmacogenomics into clinical settings, all relevant clinical recommendations pertaining to gene-drug pairs must be summarized and presented to clinicians in a manner that is seamlessly integrated into the clinical workflow of the EHR. In some situations, ancillary systems and applications outside the EHR may be integrated to augment the capabilities of the EHR.
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Affiliation(s)
- J Kevin Hicks
- DeBartolo Family Personalized Medicine Institute and Department of Population Sciences, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | | | - Karl F Gumpper
- Department of Pharmacy, Boston Children's Hospital, Boston, MA
| | - Cyrine E Haidar
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - James M Hoffman
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN.
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28
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Dunnenberger HM, Biszewski M, Bell GC, Sereika A, May H, Johnson SG, Hulick PJ, Khandekar J. Implementation of a multidisciplinary pharmacogenomics clinic in a community health system. Am J Health Syst Pharm 2018; 73:1956-1966. [PMID: 27864203 DOI: 10.2146/ajhp160072] [Citation(s) in RCA: 81] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
PURPOSE The development and implementation of a multidisciplinary pharmacogenomics clinic within the framework of an established community-based medical genetics program are described. SUMMARY Pharmacogenomics is an important component of precision medicine that holds considerable promise for pharmacotherapy optimization. As part of the development of a health system-wide integrated pharmacogenomics program, in early 2015 Northshore University Health-System established a pharmacogenomics clinic run by a multidisciplinary team including a medical geneticist, a pharmacist, a nurse practitioner, and genetic counselors. The team identified five key program elements: (1) a billable-service provider, (2) a process for documentation of relevant medication and family histories, (3) personnel with the knowledge required to interpret pharmacogenomic results, (4) personnel to discuss risks, benefits, and limitations of pharmacogenomic testing, and (5) a mechanism for reporting results. The most important program component is expert interpretation of genetic test results to provide clinically useful information; pharmacists are well positioned to provide that expertise. At the Northshore University HealthSystem pharmacogenomics clinic, patient encounters typically entail two one-hour visits and follow a standardized workflow. At the first visit, pharmacogenomics-focused medication and family histories are obtained, risks and benefits of genetic testing are explained, and a test sample is collected; at the second visit, test results are provided along with evidence-based pharmacotherapy recommendations. CONCLUSION A multidisciplinary clinic providing genotyping and related services can facilitate the integration of pharmacogenomics into clinical care and meet the needs of early adopters of precision medicine.
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Affiliation(s)
- Henry M Dunnenberger
- Center for Molecular Medicine, NorthShore University HealthSystem, Evanston, IL.
| | - Matthew Biszewski
- Thrombosis and Anticoagulation Unit, NorthShore University HealthSystem, Glenview, IL
| | | | - Annette Sereika
- Center for Molecular Medicine, NorthShore University HealthSystem, Evanston, IL
| | - Holley May
- Center for Medical Genetics, NorthShore University HealthSystem, Evanston, IL
| | | | - Peter J Hulick
- Center for Medical Genetics, NorthShore University HealthSystem, Evanston, IL
| | - Janardan Khandekar
- Center for Molecular Medicine, NorthShore University HealthSystem, Evanston, IL
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29
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Vo TT, Bell GC, Owusu Obeng A, Hicks JK, Dunnenberger HM. Pharmacogenomics Implementation: Considerations for Selecting a Reference Laboratory. Pharmacotherapy 2017; 37:1014-1022. [DOI: 10.1002/phar.1985] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Teresa T. Vo
- Department of Pharmacotherapeutics and Clinical Research; College of Pharmacy; University of South Florida; Tampa Florida
| | - Gillian C. Bell
- Personalized Medicine Program; Mission Health; Asheville North Carolina
| | - Aniwaa Owusu Obeng
- The Charles Bronfman Institute for Personalized Medicine; Icahn School of Medicine at Mount Sinai; New York New York
- Pharmacy Department; The Mount Sinai Hospital; New York New York
| | - J. Kevin Hicks
- Division of Population, Science; Department of Individualized Cancer Management; DeBartolo Family Personalized Medicine Institute; Moffitt Cancer Center & Research Institute; Tampa Florida
| | - Henry M. Dunnenberger
- Center for Molecular Medicine; NorthShore University HealthSystem; Evanston Illinois
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30
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Lemke AA, Hutten Selkirk CG, Glaser NS, Sereika AW, Wake DT, Hulick PJ, Dunnenberger HM. Primary care physician experiences with integrated pharmacogenomic testing in a community health system. Per Med 2017; 14:389-400. [DOI: 10.2217/pme-2017-0036] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Aim: To explore primary care physicians’ views of the utility and delivery of direct access to pharmacogenomics (PGx) testing in a community health system. Methods: This descriptive study assessed the perspectives of 15 healthcare providers utilizing qualitative individual interviews. Results: Three main themes emerged: perceived value and utility of PGx testing; challenges to implementation in practice; and provider as well as patient needs. Conclusion: While providers in this study viewed benefits of PGx testing as avoiding side effects, titrating doses more quickly, improving shared decision-making and providing psychological reassurance, challenges will need to be addressed such as privacy concerns, cost, insurance coverage and understanding the complexity of PGx test results.
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Affiliation(s)
- Amy A Lemke
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Christina G Hutten Selkirk
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Nicole S Glaser
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Annette W Sereika
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Dyson T Wake
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Peter J Hulick
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
| | - Henry M Dunnenberger
- Center for Personalized Medicine, NorthShore University HealthSystem, 1001 University Place, Suite 160, Evanston, IL 60201, USA
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31
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Hicks JK, Sangkuhl K, Swen JJ, Ellingrod VL, Müller DJ, Shimoda K, Bishop JR, Kharasch ED, Skaar TC, Gaedigk A, Dunnenberger HM, Klein TE, Caudle KE, Stingl JC. Clinical pharmacogenetics implementation consortium guideline (CPIC) for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants: 2016 update. Clin Pharmacol Ther 2017; 102:37-44. [PMID: 27997040 DOI: 10.1002/cpt.597] [Citation(s) in RCA: 381] [Impact Index Per Article: 54.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 11/21/2016] [Accepted: 12/07/2016] [Indexed: 11/06/2022]
Affiliation(s)
- J K Hicks
- DeBartolo Family Personalized Medicine Institute, Division of Population Science, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - K Sangkuhl
- Department of Genetics, Stanford University, Stanford, California, USA
| | - J J Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - V L Ellingrod
- Department of Clinical, Social and Administrative Sciences, College of Pharmacy, and Department of Psychiatry, School of Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - D J Müller
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - K Shimoda
- Department of Psychiatry, Dokkyo Medical University, Japan
| | - J R Bishop
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, and Department of Psychiatry, College of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
| | - E D Kharasch
- Division of Clinical and Translational Research, Department of Anesthesiology, Washington University in St, Louis, St, Louis, Missouri, USA
| | - T C Skaar
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - A Gaedigk
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy, Kansas City, Missouri and Department of Pediatrics, University of Missouri-Kansas City, Kansas City, Missouri, USA
| | - H M Dunnenberger
- Center for Molecular Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - T E Klein
- Department of Genetics, Stanford University, Stanford, California, USA
| | - K E Caudle
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - J C Stingl
- Division of Research, Federal Institute of Drugs and Medical Devices, Bonn, Germany
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32
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Caudle KE, Dunnenberger HM, Freimuth RR, Peterson JF, Burlison JD, Whirl-Carrillo M, Scott SA, Rehm HL, Williams MS, Klein TE, Relling MV, Hoffman JM. Standardizing terms for clinical pharmacogenetic test results: consensus terms from the Clinical Pharmacogenetics Implementation Consortium (CPIC). Genet Med 2017; 19:215-223. [PMID: 27441996 PMCID: PMC5253119 DOI: 10.1038/gim.2016.87] [Citation(s) in RCA: 303] [Impact Index Per Article: 43.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Accepted: 05/17/2016] [Indexed: 12/22/2022] Open
Abstract
INTRODUCTION Reporting and sharing pharmacogenetic test results across clinical laboratories and electronic health records is a crucial step toward the implementation of clinical pharmacogenetics, but allele function and phenotype terms are not standardized. Our goal was to develop terms that can be broadly applied to characterize pharmacogenetic allele function and inferred phenotypes. MATERIALS AND METHODS Terms currently used by genetic testing laboratories and in the literature were identified. The Clinical Pharmacogenetics Implementation Consortium (CPIC) used the Delphi method to obtain a consensus and agree on uniform terms among pharmacogenetic experts. RESULTS Experts with diverse involvement in at least one area of pharmacogenetics (clinicians, researchers, genetic testing laboratorians, pharmacogenetics implementers, and clinical informaticians; n = 58) participated. After completion of five surveys, a consensus (>70%) was reached with 90% of experts agreeing to the final sets of pharmacogenetic terms. DISCUSSION The proposed standardized pharmacogenetic terms will improve the understanding and interpretation of pharmacogenetic tests and reduce confusion by maintaining consistent nomenclature. These standard terms can also facilitate pharmacogenetic data sharing across diverse electronic health care record systems with clinical decision support.Genet Med 19 2, 215-223.
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Affiliation(s)
- Kelly E. Caudle
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Henry M. Dunnenberger
- Center for Molecular Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Robert R. Freimuth
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Josh F. Peterson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jonathan D. Burlison
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | | | - Stuart A. Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Heidi L. Rehm
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Marc S. Williams
- Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA
| | - Teri E. Klein
- Department of Genetics, Stanford University, Stanford, California, USA
| | - Mary V. Relling
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - James M. Hoffman
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
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33
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Schwinghammer TL, Crannage AJ, Boyce EG, Bradley B, Christensen A, Dunnenberger HM, Fravel M, Gurgle H, Hammond DA, Kwon J, Slain D, Wargo KA. The 2016 ACCP Pharmacotherapy Didactic Curriculum Toolkit. Pharmacotherapy 2016; 36:e189-e194. [PMID: 27791276 DOI: 10.1002/phar.1846] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The 2016 American College of Clinical Pharmacy (ACCP) Educational Affairs Committee was charged with updating and contemporizing ACCP's 2009 Pharmacotherapy Didactic Curriculum Toolkit. The toolkit has been designed to guide schools and colleges of pharmacy in developing, maintaining, and modifying their curricula. The 2016 committee reviewed the recent medical literature and other documents to identify disease states that are responsive to drug therapy. Diseases and content topics were organized by organ system, when feasible, and grouped into tiers as defined by practice competency. Tier 1 topics should be taught in a manner that prepares all students to provide collaborative, patient-centered care upon graduation and licensure. Tier 2 topics are generally taught in the professional curriculum, but students may require additional knowledge or skills after graduation (e.g., residency training) to achieve competency in providing direct patient care. Tier 3 topics may not be taught in the professional curriculum; thus, graduates will be required to obtain the necessary knowledge and skills on their own to provide direct patient care, if required in their practice. The 2016 toolkit contains 276 diseases and content topics, of which 87 (32%) are categorized as tier 1, 133 (48%) as tier 2, and 56 (20%) as tier 3. The large number of tier 1 topics will require schools and colleges to use creative pedagogical strategies to achieve the necessary practice competencies. Almost half of the topics (48%) are tier 2, highlighting the importance of postgraduate residency training or equivalent practice experience to competently care for patients with these disorders. The Pharmacotherapy Didactic Curriculum Toolkit will continue to be updated to provide guidance to faculty at schools and colleges of pharmacy as these academic pharmacy institutions regularly evaluate and modify their curricula to keep abreast of scientific advances and associated practice changes. Access the current Pharmacotherapy Didactic Curriculum Toolkit at http://www.accp.com/docs/positions/misc/Toolkit_final.pdf.
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Hoffman JM, Dunnenberger HM, Kevin Hicks J, Caudle KE, Whirl Carrillo M, Freimuth RR, Williams MS, Klein TE, Peterson JF. Developing knowledge resources to support precision medicine: principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC). J Am Med Inform Assoc 2016; 23:796-801. [PMID: 27026620 DOI: 10.1093/jamia/ocw027] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Accepted: 01/13/2016] [Indexed: 11/13/2022] Open
Abstract
To move beyond a select few genes/drugs, the successful adoption of pharmacogenomics into routine clinical care requires a curated and machine-readable database of pharmacogenomic knowledge suitable for use in an electronic health record (EHR) with clinical decision support (CDS). Recognizing that EHR vendors do not yet provide a standard set of CDS functions for pharmacogenetics, the Clinical Pharmacogenetics Implementation Consortium (CPIC) Informatics Working Group is developing and systematically incorporating a set of EHR-agnostic implementation resources into all CPIC guidelines. These resources illustrate how to integrate pharmacogenomic test results in clinical information systems with CDS to facilitate the use of patient genomic data at the point of care. Based on our collective experience creating existing CPIC resources and implementing pharmacogenomics at our practice sites, we outline principles to define the key features of future knowledge bases and discuss the importance of these knowledge resources for pharmacogenomics and ultimately precision medicine.
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Affiliation(s)
- James M Hoffman
- Department of Pharmaceutical Sciences, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Henry M Dunnenberger
- Center for Molecular Medicine, NorthShore University HealthSystem, Evanston, IL, USA
| | - J Kevin Hicks
- Pharmacy Department and Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Kelly E Caudle
- Department of Pharmaceutical Sciences, St Jude Children's Research Hospital, Memphis, TN, USA
| | | | - Robert R Freimuth
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Marc S Williams
- Genomic Medicine Institute, Geisinger Health System, Danville, PA, USA
| | - Teri E Klein
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Josh F Peterson
- Departments of Medicine and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
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Affiliation(s)
- Henry M Dunnenberger
- Molecular Medicine Center, NorthShore University HealthSystem, Evanston, Illinois
| | - Janardan D Khandekar
- Molecular Medicine Center, NorthShore University HealthSystem, Evanston, Illinois
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Crews KR, Caudle KE, Dunnenberger HM, Sadhasivam S, Skaar TC. Considerations for the Utility of the CPIC Guideline for CYP2D6 Genotype and Codeine Therapy. Clin Chem 2015; 61:775-6. [PMID: 25770140 DOI: 10.1373/clinchem.2014.237412] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Kristine R Crews
- Department of Pharmaceutical Sciences St. Jude Children's Research Hospital Memphis, TN
| | - Kelly E Caudle
- Department of Pharmaceutical Sciences St. Jude Children's Research Hospital Memphis, TN
| | | | - Senthilkumar Sadhasivam
- Department of Pediatrics and Department of Anesthesia Cincinnati Children's Hospital Medical Center Cincinnati, OH
| | - Todd C Skaar
- Division of Clinical Pharmacology Department of Medicine Indiana University School of Medicine Indianapolis, IN
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Dunnenberger HM, Crews KR, Hoffman JM, Caudle KE, Broeckel U, Howard SC, Hunkler RJ, Klein TE, Evans WE, Relling MV. Preemptive clinical pharmacogenetics implementation: current programs in five US medical centers. Annu Rev Pharmacol Toxicol 2014; 55:89-106. [PMID: 25292429 DOI: 10.1146/annurev-pharmtox-010814-124835] [Citation(s) in RCA: 331] [Impact Index Per Article: 33.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Although the field of pharmacogenetics has existed for decades, practioners have been slow to implement pharmacogenetic testing in clinical care. Numerous publications describe the barriers to clinical implementation of pharmacogenetics. Recently, several freely available resources have been developed to help address these barriers. In this review, we discuss current programs that use preemptive genotyping to optimize the pharmacotherapy of patients. Array-based preemptive testing includes a large number of relevant pharmacogenes that impact multiple high-risk drugs. Using a preemptive approach allows genotyping results to be available prior to any prescribing decision so that genomic variation may be considered as an inherent patient characteristic in the planning of therapy. This review describes the common elements among programs that have implemented preemptive genotyping and highlights key processes for implementation, including clinical decision support.
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Crews KR, Gaedigk A, Dunnenberger HM, Leeder JS, Klein TE, Caudle KE, Haidar CE, Shen DD, Callaghan JT, Sadhasivam S, Prows CA, Kharasch ED, Skaar TC. Clinical Pharmacogenetics Implementation Consortium guidelines for cytochrome P450 2D6 genotype and codeine therapy: 2014 update. Clin Pharmacol Ther 2014; 95:376-82. [PMID: 24458010 DOI: 10.1038/clpt.2013.254] [Citation(s) in RCA: 453] [Impact Index Per Article: 45.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2013] [Accepted: 12/17/2013] [Indexed: 11/09/2022]
Abstract
Codeine is bioactivated to morphine, a strong opioid agonist, by the hepatic cytochrome P450 2D6 (CYP2D6); hence, the efficacy and safety of codeine are governed by CYP2D6 activity. Polymorphisms are a major cause of CYP2D6 variability. We summarize evidence from the literature supporting this association and provide therapeutic recommendations for codeine based on CYP2D6 genotype. This document is an update to the 2012 Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for CYP2D6 genotype and codeine therapy.
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Affiliation(s)
- K R Crews
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - A Gaedigk
- 1] Division of Clinical Pharmacology and Therapeutic Innovation, Children's Mercy Hospitals and Clinics, Kansas City, Missouri, USA [2] Department of Pediatrics, University of Missouri-Kansas City, Kansas City, Missouri, USA
| | - H M Dunnenberger
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - J S Leeder
- 1] Division of Clinical Pharmacology and Therapeutic Innovation, Children's Mercy Hospitals and Clinics, Kansas City, Missouri, USA [2] Department of Pediatrics, University of Missouri-Kansas City, Kansas City, Missouri, USA
| | - T E Klein
- Department of Genetics, Stanford University, Stanford, California, USA
| | - K E Caudle
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - C E Haidar
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - D D Shen
- 1] Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington, USA [2] Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, Washington, USA
| | - J T Callaghan
- 1] Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA [2] Department of Veterans Affairs, RLR VA Medical Center, Indianapolis, Indiana, USA
| | - S Sadhasivam
- 1] Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA [2] Department of Anesthesia, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - C A Prows
- 1] Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA [2] Division of Patient Services, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - E D Kharasch
- Division of Clinical and Translational Research, Department of Anesthesiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - T C Skaar
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
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Leckband SG, Kelsoe JR, Dunnenberger HM, George AL, Tran E, Berger R, Müller DJ, Whirl-Carrillo M, Caudle KE, Pirmohamed M. Clinical Pharmacogenetics Implementation Consortium guidelines for HLA-B genotype and carbamazepine dosing. Clin Pharmacol Ther 2013; 94:324-8. [PMID: 23695185 DOI: 10.1038/clpt.2013.103] [Citation(s) in RCA: 175] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2013] [Accepted: 05/09/2013] [Indexed: 01/31/2023]
Abstract
Human leukocyte antigen B (HLA-B) is a gene that encodes a cell surface protein involved in presenting antigens to the immune system. The variant allele HLA-B*15:02 is associated with an increased risk of Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) in response to carbamazepine treatment. We summarize evidence from the published literature supporting this association and provide recommendations for the use of carbamazepine based on HLA-B genotype (also available on PharmGKB: http://www.pharmgkb.org). The purpose of this article is to provide information to allow the interpretation of clinical HLA-B*15:02 genotype tests so that the results can be used to guide the use of carbamazepine. The guideline provides recommendations for the use of carbamazepine when HLA-B*15:02 genotype results are available. Detailed guidelines regarding the selection of alternative therapies, the use of phenotypic tests, when to conduct genotype testing, and cost-effectiveness analyses are beyond the scope of this document. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines are published and updated periodically on the PharmGKB website at (http://www.pharmgkb.org).
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Affiliation(s)
- S G Leckband
- Veterans Affairs San Diego Healthcare System, San Diego, California, USA
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Crews KR, Gaedigk A, Dunnenberger HM, Klein TE, Shen DD, Callaghan JT, Kharasch ED, Skaar TC. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for codeine therapy in the context of cytochrome P450 2D6 (CYP2D6) genotype. Clin Pharmacol Ther 2011; 91:321-6. [PMID: 22205192 DOI: 10.1038/clpt.2011.287] [Citation(s) in RCA: 282] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Codeine is bioactivated to morphine, a strong opioid agonist, by the hepatic cytochrome P450 2D6 (CYP2D6); hence, the efficacy and safety of codeine as an analgesic are governed by CYP2D6 polymorphisms. Codeine has little therapeutic effect in patients who are CYP2D6 poor metabolizers, whereas the risk of morphine toxicity is higher in ultrarapid metabolizers. The purpose of this guideline (periodically updated at http://www.pharmgkb.org) is to provide information relating to the interpretation of CYP2D6 genotype test results to guide the dosing of codeine.
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Affiliation(s)
- K R Crews
- Department of Pharmaceutical Sciences, St Jude Children's Research Hospital, Memphis, Tennessee, USA.
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