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Grande KJ, Dalton R, Moyer NA, Arwood MJ, Nguyen KA, Sumfest J, Ashcraft KC, Cooper-DeHoff RM. Assessment of a Manual Method versus an Automated, Probability-Based Algorithm to Identify Patients at High Risk for Pharmacogenomic Adverse Drug Outcomes in a University-Based Health Insurance Program. J Pers Med 2022; 12:jpm12020161. [PMID: 35207649 PMCID: PMC8878761 DOI: 10.3390/jpm12020161] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 12/21/2021] [Accepted: 12/29/2021] [Indexed: 12/21/2022] Open
Abstract
We compared patient cohorts selected for pharmacogenomic testing using a manual method or automated algorithm in a university-based health insurance network. The medication list was compiled from claims data during 4th quarter 2018. The manual method selected patients by number of medications by the health system’s list of medications for pharmacogenomic testing. The automated method used YouScript’s pharmacogenetic interaction probability (PIP) algorithm to select patients based on the probability that testing would result in detection of one or more clinically significant pharmacogenetic interactions. A total of 6916 patients were included. Patient cohorts selected by each method differed substantially, including size (manual n = 218, automated n = 286) and overlap (n = 41). The automated method was over twice as likely to identify patients where testing may reveal a clinically significant pharmacogenetic interaction than the manual method (62% vs. 29%, p < 0.0001). The manual method captured more patients with significant drug–drug or multi-drug interactions (80.3% vs. 40.2%, respectively, p < 0.0001), higher average number of significant drug interactions per patient (3.3 vs. 1.1, p < 0.0001), and higher average number of unique medications per patient (9.8 vs. 7.4, p < 0.0001). It is possible to identify a cohort of patients who would likely benefit from pharmacogenomic testing using manual or automated methods.
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Affiliation(s)
| | - Rachel Dalton
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA; (R.D.); (K.A.N.)
| | | | | | - Khoa A. Nguyen
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA; (R.D.); (K.A.N.)
| | - Jill Sumfest
- GatorCare, University of Florida, Gainesville, FL 32610, USA;
| | | | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA; (R.D.); (K.A.N.)
- Division of Cardiology, College of Medicine, University of Florida, Gainesville, FL 32610, USA
- Correspondence: ; Tel.: +1-352-359-2658
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52
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Selig DJ, Livezey JR, Chin GC, DeLuca JP, Guillory Ii WO, Kress AT, Oliver TO, Por ED. Prescription Patterns and Relationship to Pharmacogenomics Testing in the Military Health System. Mil Med 2021; 187:9-17. [PMID: 34967405 DOI: 10.1093/milmed/usab481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/21/2021] [Accepted: 12/03/2021] [Indexed: 11/12/2022] Open
Abstract
INTRODUCTION Clinical utilization of pharmacogenomics (PGx) testing is highly institutionally dependent, and little information is known about provider practices of PGx testing in the Military Health System (MHS). In this study, we aimed to characterize Clinical Pharmacogenetics Implementation Consortium (CPIC) actionable prescription (Rx) patterns and their temporal relationship with PGx testing in the MHS. METHODS Using data from the Military Health System Management Analysis and Reporting Tool (M2) database, this retrospective cohort study included all patients receiving at least one PGx test and at least one CPIC actionable Rx from January 2015 to August 2020 (845 patients, 1,471 PGx, 7,725 index CPIC actionable Rxs). Rx patterns and temporal relationships with PGx testing were characterized via descriptive statistics. Binomial regression was used to determine which patient and provider characteristics were associated with a patient receiving a PGx test within 30 days of an index Rx. RESULTS Patients had a median of 9 index CPIC actionable Rx's (range 1-26). Pain medications were most commonly prescribed (N = 794, 94% patients with at least 1 Rx). However, pain medication had the lowest Rx-PGx match rate (40%) compared to an average of 62% Rx-PGx match rate for all CPIC drugs. Antidepressants were also commonly prescribed (N = 668, 79.1% patients with at least 1 Rx), and antidepressants had the highest Rx-PGx match rate of 86.7%. A minority of providers (20%, N = 249) ordered the majority of PGx tests (86.1%, N = 1,266) and only 8.3% of PGx tests (N = 398) matched to a CPIC actionable drug within 30 days of the test (defined by Rxs ordered within 30 days before or after the PGx test). However, approximately 39.8% of patients (N = 317) had at least one drug match to a PGx test within 30 days. The largest predictor of whether a patient received a PGx test within 30 days of any index Rx was whether or not a specific psychiatry provider ordered the PGx test (odds ratio; OR 3.7, 95% CI 2.13-6.54, P < 0.001). Neither the CPIC level of evidence nor FDA PGx actionable or informative labels had a significant effect on PGx test timing. CONCLUSIONS PGx testing was generally limited to high Rx-drug users and was found to be an under-utilized resource. PGx testing did not typically follow CPIC guidelines. Implementing PGx testing protocols, simplifying PGx test-ordering by incorporating at minimum CYP2D6, CYP2C19, and CYP2C9 into PGx-testing panels, and unifying providers' PGx knowledgebase in the MHS are feasible and would improve the clinical utilization of PGx tests in the MHS.
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Affiliation(s)
- Daniel J Selig
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| | - Jeffrey R Livezey
- Clinical Pharmacology Department, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Geoffrey C Chin
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| | - Jesse P DeLuca
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| | - Walter O Guillory Ii
- The Internal Medicine Department, Walter Reed National Military Medical Center, Bethesda, MD 20814, USA
| | - Adrian T Kress
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| | - Thomas O Oliver
- Clinical Pharmacology Department, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Elaine D Por
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
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53
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Gammal RS, Berenbrok LA, Empey PE, Massart MB. Documenting Pharmacogenomic Test Results in Electronic Health Records: Practical Considerations for Primary Care Teams. J Pers Med 2021; 11:jpm11121296. [PMID: 34945768 PMCID: PMC8706275 DOI: 10.3390/jpm11121296] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 11/26/2021] [Accepted: 11/29/2021] [Indexed: 12/21/2022] Open
Abstract
With increasing patient interest in and access to pharmacogenomic testing, clinicians practicing in primary care are more likely than ever to encounter a patient seeking or presenting with pharmacogenomic test results. Gene-based prescribing recommendations are available to healthcare providers through Food and Drug Administration-approved drug labeling and Clinical Pharmacogenetics Implementation Consortium guidelines. Given the lifelong utility of pharmacogenomic test results to optimize pharmacotherapy for commonly prescribed medications, appropriate documentation of these results in a patient’s electronic health record (EHR) is essential. The current “gold standard” for pharmacogenomics implementation includes entering pharmacogenomic test results into EHRs as discrete results with associated clinical decision support (CDS) alerts that will fire at the point of prescribing, similar to drug allergy alerts. However, such infrastructure is limited to the few institutions that have invested in the resources and personnel to develop and maintain it. For the majority of clinicians who do not practice at an institution with a dedicated clinical pharmacogenomics team and integrated pharmacogenomics CDS in the EHR, this report provides practical tips for documenting pharmacogenomic test results in the problem list and allergy field to maximize the visibility and utility of results over time, especially when such results could prevent the occurrence of serious adverse drug reactions or predict therapeutic failure.
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Affiliation(s)
- Roseann S. Gammal
- Department of Pharmacy Practice, Massachusetts College of Pharmacy and Health Sciences, Boston, MA 02115, USA;
| | - Lucas A. Berenbrok
- Department of Pharmacy and Therapeutics, University of Pittsburgh School of Pharmacy, Pittsburgh, PA 15261, USA; (L.A.B.); (P.E.E.)
| | - Philip E. Empey
- Department of Pharmacy and Therapeutics, University of Pittsburgh School of Pharmacy, Pittsburgh, PA 15261, USA; (L.A.B.); (P.E.E.)
| | - Mylynda B. Massart
- Department of Family Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
- Correspondence: ; Tel.: +1-503-939-7261
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54
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Ashcraft K, Moretz C, Schenning C, Rojahn S, Vines Tanudtanud K, Magoncia GO, Reyes J, Marquez B, Guo Y, Erdemir ET, Hall TO. Unmanaged Pharmacogenomic and Drug Interaction Risk Associations with Hospital Length of Stay among Medicare Advantage Members with COVID-19: A Retrospective Cohort Study. J Pers Med 2021; 11:jpm11111192. [PMID: 34834543 PMCID: PMC8617857 DOI: 10.3390/jpm11111192] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 11/02/2021] [Accepted: 11/09/2021] [Indexed: 12/12/2022] Open
Abstract
Unmanaged pharmacogenomic and drug interaction risk can lengthen hospitalization and may have influenced the severe health outcomes seen in some COVID-19 patients. To determine if unmanaged pharmacogenomic and drug interaction risks were associated with longer lengths of stay (LOS) among patients hospitalized with COVID-19, we retrospectively reviewed medical and pharmacy claims from 6025 Medicare Advantage members hospitalized with COVID-19. Patients with a moderate or high pharmacogenetic interaction probability (PIP), which indicates the likelihood that testing would identify one or more clinically actionable gene–drug or gene–drug–drug interactions, were hospitalized for 9% (CI: 4–15%; p < 0.001) and 16% longer (CI: 8–24%; p < 0.001), respectively, compared to those with low PIP. Risk adjustment factor (RAF) score, a commonly used measure of disease burden, was not associated with LOS. High PIP was significantly associated with 12–22% longer LOS compared to low PIP in patients with hypertension, hyperlipidemia, diabetes, or chronic obstructive pulmonary disease (COPD). A greater drug–drug interaction risk was associated with 10% longer LOS among patients with two or three chronic conditions. Thus, unmanaged pharmacogenomic risk was associated with longer LOS in these patients and managing this risk has the potential to reduce LOS in severely ill patients, especially those with chronic conditions.
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Affiliation(s)
- Kristine Ashcraft
- Invitae Corporation, San Francisco, CA 94103, USA; (C.M.); (C.S.); (S.R.)
- Correspondence: ; Tel.: +1-415-374-7782
| | - Chad Moretz
- Invitae Corporation, San Francisco, CA 94103, USA; (C.M.); (C.S.); (S.R.)
| | | | - Susan Rojahn
- Invitae Corporation, San Francisco, CA 94103, USA; (C.M.); (C.S.); (S.R.)
| | - Kae Vines Tanudtanud
- OptumLabs at UnitedHealth Group, Minnetonka, MN 55343, USA; (K.V.T.); (G.O.M.); (J.R.); (B.M.); (Y.G.); (E.T.E.); (T.O.H.)
| | - Gwyn Omar Magoncia
- OptumLabs at UnitedHealth Group, Minnetonka, MN 55343, USA; (K.V.T.); (G.O.M.); (J.R.); (B.M.); (Y.G.); (E.T.E.); (T.O.H.)
| | - Justine Reyes
- OptumLabs at UnitedHealth Group, Minnetonka, MN 55343, USA; (K.V.T.); (G.O.M.); (J.R.); (B.M.); (Y.G.); (E.T.E.); (T.O.H.)
| | - Bernardo Marquez
- OptumLabs at UnitedHealth Group, Minnetonka, MN 55343, USA; (K.V.T.); (G.O.M.); (J.R.); (B.M.); (Y.G.); (E.T.E.); (T.O.H.)
| | - Yinglong Guo
- OptumLabs at UnitedHealth Group, Minnetonka, MN 55343, USA; (K.V.T.); (G.O.M.); (J.R.); (B.M.); (Y.G.); (E.T.E.); (T.O.H.)
| | - Elif Tokar Erdemir
- OptumLabs at UnitedHealth Group, Minnetonka, MN 55343, USA; (K.V.T.); (G.O.M.); (J.R.); (B.M.); (Y.G.); (E.T.E.); (T.O.H.)
| | - Taryn O. Hall
- OptumLabs at UnitedHealth Group, Minnetonka, MN 55343, USA; (K.V.T.); (G.O.M.); (J.R.); (B.M.); (Y.G.); (E.T.E.); (T.O.H.)
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Lunenburg CATC, Ishtiak-Ahmed K, Werge T, Gasse C. Life-time Actionable Pharmacogenetic Drug Use: A Population-based Cohort Study in 86 040 Young People With and Without Mental Disorders in Denmark. PHARMACOPSYCHIATRY 2021; 55:95-107. [PMID: 34753194 PMCID: PMC8964272 DOI: 10.1055/a-1655-9500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Objective
To describe life-time use of current actionable pharmacogenetic
(PGx) somatic and psychotropic drugs according to international PGx consortia in
people with and without hospital-diagnosed mental disorders in the Danish
population.
Methods
Population- and register-based observational drug utilization
study in 56 065 individuals with mental disorders, i. e.
attention-deficit/hyperactivity disorder, autism, bipolar disorder,
depression and schizophrenia, and a random, representative sample of
29 975 individuals of the Danish population, born between 1981 and 2005.
Individuals were followed from 1995 or birth until 2016 (for a maximum of 22
years). We report prevalence and incidence rates of PGx drug use by age, sex and
mental disorders based on redeemed prescriptions between 1995 and 2016.
Results
Of the 69 PGx drugs, prescriptions of 39 drugs had been redeemed
by the study population by 35 years of age. The use of at least 1 PGx drug
varied between 23.1% in males without mental disorders and 97.2%
in females with schizophrenia. Males with ADHD or autism were the youngest
first-time PGx drug users at a mean of 11.6 years. The mean number of different
PGx drugs used was 1.2 in males without mental disorders and 5.6 in individuals
with schizophrenia. The prevalence of different PGx drugs linked to more than
one gene was 25.3% in males without mental disorders to 94.1% in
females with schizophrenia.
Conclusion
PGx drugs are commonly used by younger people, more often by
individuals with mental disorders and by females. Panel-based PGx testing could
contribute to treatment decisions at a very young age.
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Affiliation(s)
- Carin A T C Lunenburg
- Department of Affective Disorders, Aarhus University Hospital Psychiatry, Aarhus, Denmark.,Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Kazi Ishtiak-Ahmed
- Department of Affective Disorders, Aarhus University Hospital Psychiatry, Aarhus, Denmark.,Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Copenhagen, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.,Lundbeck Foundation Center for GeoGenetics, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.,The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Copenhagen, Denmark
| | - Christiane Gasse
- Department of Affective Disorders, Aarhus University Hospital Psychiatry, Aarhus, Denmark.,Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.,Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark.,Centre for Integrated Register-based Research Aarhus University (CIRRAU), Aarhus, Denmark
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56
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Brunette CA, Dong OM, Vassy JL, Danowski ME, Alexander N, Antwi AA, Christensen KD. A Cost-Consequence Analysis of Preemptive SLCO1B1 Testing for Statin Myopathy Risk Compared to Usual Care. J Pers Med 2021; 11:1123. [PMID: 34834475 PMCID: PMC8624003 DOI: 10.3390/jpm11111123] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 10/27/2021] [Accepted: 10/29/2021] [Indexed: 11/16/2022] Open
Abstract
There is a well-validated association between SLCO1B1 (rs4149056) and statin-associated muscle symptoms (SAMS). Preemptive SLCO1B1 pharmacogenetic (PGx) testing may diminish the incidence of SAMS by identifying individuals with increased genetic risk before statin initiation. Despite its potential clinical application, the cost implications of SLCO1B1 testing are largely unknown. We conducted a cost-consequence analysis of preemptive SLCO1B1 testing (PGx+) versus usual care (PGx-) among Veteran patients enrolled in the Integrating Pharmacogenetics in Clinical Care (I-PICC) Study. The assessment was conducted using a health system perspective and 12-month time horizon. Incremental costs of SLCO1B1 testing and downstream medical care were estimated using data from the U.S. Department of Veterans Affairs' Managerial Cost Accounting System. A decision analytic model was also developed to model 1-month cost and SAMS-related outcomes in a hypothetical cohort of 10,000 Veteran patients, where all patients were initiated on simvastatin. Over 12 months, 13.5% of PGx+ (26/193) and 11.2% of PGx- (24/215) participants in the I-PICC Study were prescribed Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline-concordant statins (Δ2.9%, 95% CI -4.0% to 10.0%). Differences in mean per-patient costs for lipid therapy prescriptions, including statins, for PGx+ compared to PGx- participants were not statistically significant (Δ USD 9.53, 95% CI -0.86 to 22.80 USD). Differences in per-patient costs attributable to the intervention, including PGx testing, lipid-lowering prescriptions, SAMS, laboratory and imaging expenses, and primary care and cardiology services, were also non-significant (Δ- USD 1004, 95% CI -2684 to 1009 USD). In the hypothetical cohort, SLCO1B1-informed statin therapy averted 109 myalgias and 3 myopathies at 1-month follow up. Fewer statin discontinuations (78 vs. 109) were also observed, but the SLCO1B1 testing strategy was 96 USD more costly per patient compared to no testing (124 vs. 28 USD). The implementation of SLCO1B1 testing resulted in small, non-significant increases in the proportion of patients receiving CPIC-concordant statin prescriptions within a real-world primary care context, diminished the incidence of SAMS, and reduced statin discontinuations in a hypothetical cohort of 10,000 patients. Despite these effects, SLCO1B1 testing administered as a standalone test did not result in lower per-patient health care costs at 1 month or over 1 year of treatment. The inclusion of SLCO1B1, among other well-validated pharmacogenes, into preemptive panel-based testing strategies may provide a better balance of clinical benefit and cost.
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Affiliation(s)
- Charles A. Brunette
- Veterans Affairs Boston Healthcare System, Boston, MA 02130, USA; (J.L.V.); (M.E.D.); (N.A.); (A.A.A.)
| | - Olivia M. Dong
- Duke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC 27705, USA;
- Durham VA Health Care System, Durham, NC 27705, USA
| | - Jason L. Vassy
- Veterans Affairs Boston Healthcare System, Boston, MA 02130, USA; (J.L.V.); (M.E.D.); (N.A.); (A.A.A.)
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA;
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA 02115, USA
- Population Precision Health, Ariadne Labs, Boston, MA 02215, USA
| | - Morgan E. Danowski
- Veterans Affairs Boston Healthcare System, Boston, MA 02130, USA; (J.L.V.); (M.E.D.); (N.A.); (A.A.A.)
| | - Nicholas Alexander
- Veterans Affairs Boston Healthcare System, Boston, MA 02130, USA; (J.L.V.); (M.E.D.); (N.A.); (A.A.A.)
| | - Ashley A. Antwi
- Veterans Affairs Boston Healthcare System, Boston, MA 02130, USA; (J.L.V.); (M.E.D.); (N.A.); (A.A.A.)
| | - Kurt D. Christensen
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA;
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
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57
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Dong OM, Roberts MC, Wu RR, Voils CI, Sperber N, Gavin KL, Bates J, Chanfreau-Coffinier C, Naglich M, Kelley MJ, Vassy JL, Sriram P, Heise CW, Rivas S, Ribeiro M, Chapman JG, Voora D. Evaluation of the Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program at initial test sites. Pharmacogenomics 2021; 22:1121-1133. [PMID: 34704830 DOI: 10.2217/pgs-2021-0089] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: The first Plan-Do-Study-Act cycle for the Veterans Affairs Pharmacogenomic Testing for Veterans pharmacogenomic clinical testing program is described. Materials & methods: Surveys evaluating implementation resources and processes were distributed to implementation teams, providers, laboratory and health informatics staff. Survey responses were mapped to the Consolidated Framework for Implementation Research constructs to identify implementation barriers. The Expert Recommendation for Implementing Change strategies were used to address implementation barriers. Results: Survey response rate was 23-73% across personnel groups at six Veterans Affairs sites. Nine Consolidated Framework for Implementation Research constructs were most salient implementation barriers. Program revisions addressed these barriers using the Expert Recommendation for Implementing Change strategies related to three domains. Conclusion: Beyond providing free pharmacogenomic testing, additional implementation barriers need to be addressed for improved program uptake.
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Affiliation(s)
- Olivia M Dong
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
| | - Megan C Roberts
- Division of Pharmaceutical Outcomes & Policy, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - R Ryanne Wu
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
| | - Corrine I Voils
- William S Middleton Memorial Veterans Hospital, Madison, WI 53705, USA.,Department of Surgery, University of Wisconsin School of Medicine & Public Health, Madison, WI 53792, USA
| | - Nina Sperber
- Duke Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27701, USA
| | - Kara L Gavin
- William S Middleton Memorial Veterans Hospital, Madison, WI 53705, USA.,Department of Surgery, University of Wisconsin School of Medicine & Public Health, Madison, WI 53792, USA
| | - Jill Bates
- Durham VA Health Care System, Durham, NC 27705, USA.,Division of Practice Advancement & Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Catherine Chanfreau-Coffinier
- VA Informatics & Computing Infrastructure (VINCI), Salt Lake City VA Health Care System, Salt Lake City, UT 84148, USA
| | - Michael Naglich
- Institute for Medical Research, Durham VA Medical Center, Durham, NC 27705, USA
| | - Michael J Kelley
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke University Medical Center, Durham, NC 27708, USA.,National Oncology Program Office, Office of Specialty Care, Department of Veterans Affairs, Durham, NC 27705, USA
| | - Jason L Vassy
- VA Boston Healthcare System, Boston, MA 02130, USA.,Harvard Medical School, Boston, MA 02115, USA
| | - Peruvemba Sriram
- North Florida/South Georgia Veterans Health System, Gainesville, FL 32608, USA
| | - C William Heise
- Phoenix VA Health Care System, Phoenix, AZ 85012, USA.,The University of Arizona College of Medicine - Phoenix, Phoenix, AZ 85004, USA
| | - Salvador Rivas
- Phoenix VA Health Care System, Phoenix, AZ 85012, USA.,The University of Arizona College of Medicine - Phoenix, Phoenix, AZ 85004, USA
| | - Maria Ribeiro
- Atlanta VA Medical Center, Atlanta, GA 30033, USA.,Department of Hematology & Medical Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jennifer G Chapman
- Institute for Medical Research, Durham VA Medical Center, Durham, NC 27705, USA
| | - Deepak Voora
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
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58
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Affiliation(s)
- Howard S Kim
- Department of Emergency Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Center for Health Services and Outcomes Research, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Associate Editor, JAMA Network Open
| | - Danielle M McCarthy
- Department of Emergency Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Center for Health Services and Outcomes Research, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Patrick M Lank
- Department of Emergency Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Toxikon Consortium, Chicago, Illinois
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Haidar CE, Petry N, Oxencis C, Douglas JS, Hoffman JM. ASHP Statement on the Pharmacist's Role in Clinical Pharmacogenomics. Am J Health Syst Pharm 2021; 79:704-707. [PMID: 34487145 DOI: 10.1093/ajhp/zxab339] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Affiliation(s)
| | - Natasha Petry
- North Dakota State University, Sanford Health, Fargo, ND, USA
| | | | - Janine S Douglas
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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60
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Hicks JK, El Rouby N, Ong HH, Schildcrout JS, Ramsey LB, Shi Y, Tang LA, Aquilante CL, Beitelshees AL, Blake KV, Cimino JJ, Davis BH, Empey PE, Kao DP, Lemkin DL, Limdi NA, Lipori GP, Rosenman MB, Skaar TC, Teal E, Tuteja S, Wiley LK, Williams H, Winterstein AG, Van Driest SL, Cavallari LH, Peterson JF. Opportunity for Genotype-Guided Prescribing Among Adult Patients in 11 US Health Systems. Clin Pharmacol Ther 2021; 110:179-188. [PMID: 33428770 PMCID: PMC8217370 DOI: 10.1002/cpt.2161] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 12/24/2020] [Indexed: 12/11/2022]
Abstract
The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing.
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Affiliation(s)
- J. Kevin Hicks
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Nihal El Rouby
- Department of Pharmacotherapy & Translational Research, University of Florida, Gainesville, FL
- James Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH
| | - Henry H. Ong
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN
| | | | - Laura B. Ramsey
- Department of Pediatrics, College of Medicine, University of Cincinnati, Divisions of Research in Patient Services and Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Yaping Shi
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Leigh Anne Tang
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Christina L. Aquilante
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, CO
| | | | | | - James J. Cimino
- Informatics Institute, University of Alabama at Birmingham, Birmingham, AL
| | - Brittney H. Davis
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL
| | - Philip E. Empey
- Department of Pharmacy & Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA
| | - David P. Kao
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | | | - Nita A. Limdi
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL
| | - Gloria P. Lipori
- University of Florida Health and University of Florida Health Sciences Center, Gainesville, FL
| | - Marc B. Rosenman
- Indiana University School of Medicine, Indianapolis, IN
- Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL
| | - Todd C. Skaar
- Indiana University School of Medicine, Indianapolis, IN
| | | | - Sony Tuteja
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Laura K. Wiley
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | | | - Almut G. Winterstein
- Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, FL
| | - Sara L. Van Driest
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Larisa H. Cavallari
- Department of Pharmacotherapy & Translational Research, University of Florida, Gainesville, FL
| | - Josh F. Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
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Dorfman R, London Z, Metias M, Kabakchiev B, Mukerjee G, Moser A. Individualized Medication Management in Ontario Long-Term Care Clinical Impact on Management of Depression, Pain, and Dementia. J Am Med Dir Assoc 2021; 21:823-829.e5. [PMID: 32536434 DOI: 10.1016/j.jamda.2020.04.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 02/20/2020] [Accepted: 04/08/2020] [Indexed: 12/31/2022]
Abstract
OBJECTIVES Assess the potential benefits of identifying drug-gene interactions in nursing home (NH) residents on multiple medications. Reduce the use of high-risk medications for residents with reduced drug metabolism. DESIGN Open-label, nonrandomized, mixed methods study. SETTING Four NHs in Ontario. MEASUREMENTS Potential drug therapy problems (DTPs) for study cohort were identified during a medication review by a pharmacist using pharmacogenetic (PGx) clinical decision support to identify medication change opportunities. The number of DTPs identified during a standard medication review was compared with the number of DTPs identified with a PGx clinical decision support. Analysis of medication dispensing data at enrollment compared with dispensing in a 60-day window following medication review were compared for the PGx-tested study cohort with controls. RESULTS Prescription patterns of 90 study participants were compared with 895 controls for the same time period. Study participants were on 7 to 47 drugs, of which drugs with PGx indications ranged from 1 to 17 medications. The average medication load was 4.6 medications with PGx indications per person, whereas the controls were on 3.5 PGx drugs. Furthermore, 94% of cases and 84% of controls were on 2 or more drugs with PGx indication during the study period. Pharmacogenetic analysis identified 114 distinct DTPs in the 90 study participants, of which 29 were classified as serious. In this study, over 35% of residents were treated with antidepressants; of these, 64% have altered CYP2C19 or CYP2D6 metabolism and could benefit from drug dose adjustment or from a switch to alternative antidepressants. Twenty percent of residents were treated with hydromorphone, of which 30% have reduced response to opioids because of variations in the OPRM1 gene. CONCLUSIONS AND IMPLICATIONS This study demonstrated the clinical potential of PGx-based medication optimization for NH residents, impacting the management of depression, chronic pain, heart disease, and gastrointestinal symptoms.
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Affiliation(s)
- Ruslan Dorfman
- GeneYouIn Inc, Toronto, Ontario, Canada; Department of Anesthesia, McMaster University Hamilton, Ontario, Canada
| | | | | | | | | | - Andrea Moser
- Baycrest Center for Geriatric Care, Toronto, Ontario, Canada; Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada.
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Taylor ZL, Vang J, Lopez-Lopez E, Oosterom N, Mikkelsen T, Ramsey LB. Systematic Review of Pharmacogenetic Factors That Influence High-Dose Methotrexate Pharmacokinetics in Pediatric Malignancies. Cancers (Basel) 2021; 13:cancers13112837. [PMID: 34200242 PMCID: PMC8201112 DOI: 10.3390/cancers13112837] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/27/2021] [Accepted: 06/02/2021] [Indexed: 02/07/2023] Open
Abstract
Methotrexate (MTX) is a mainstay therapeutic agent administered at high doses for the treatment of pediatric and adult malignancies, such as acute lymphoblastic leukemia, osteosarcoma, and lymphoma. Despite the vast evidence for clinical efficacy, high-dose MTX displays significant inter-individual pharmacokinetic variability. Delayed MTX clearance can lead to prolonged, elevated exposure, causing increased risks for nephrotoxicity, mucositis, seizures, and neutropenia. Numerous pharmacogenetic studies have investigated the effects of several genes and polymorphisms on MTX clearance in an attempt to better understand the pharmacokinetic variability and improve patient outcomes. To date, several genes and polymorphisms that affect MTX clearance have been identified. However, evidence for select genes have conflicting results or lack the necessary replication and validation needed to confirm their effects on MTX clearance. Therefore, we performed a systematic review to identify and then summarize the pharmacogenetic factors that influence high-dose MTX pharmacokinetics in pediatric malignancies. Using the PRISMA guidelines, we analyzed 58 articles and 24 different genes that were associated with transporter pharmacology or the folate transport pathway. We conclude that there is only one gene that reliably demonstrates an effect on MTX pharmacokinetics: SLCO1B1.
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Affiliation(s)
- Zachary L. Taylor
- Department of Pharmacology and Systems Physiology, University of Cincinnati, Cincinnati, OH 45267, USA;
- Division of Research in Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
- Division of Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Jesper Vang
- Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark;
- Paediatric Oncology Research Laboratory, University Hospital of Copenhagen, Rigshospitalet Blegdamsvej 9, 2100 Copenhagen, Denmark
| | - Elixabet Lopez-Lopez
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country, UPV/EHU, 48940 Leioa, Spain;
- Pediatric Oncology Group, BioCruces Bizkaia Health Research Institute, 48903 Barakaldo, Spain
| | - Natanja Oosterom
- Princess Máxima Center for Pediatric Oncology, 3720 Utrecht, The Netherlands;
| | - Torben Mikkelsen
- Department of Pediatric Oncology, Aarhus University Hospital, 8200 Aarhus, Denmark;
| | - Laura B. Ramsey
- Division of Research in Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
- Division of Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
- Correspondence: ; Tel.: +1-513-803-8963
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Wendt FR, Koller D, Pathak GA, Jacoby D, Miller EJ, Polimanti R. Biobank Scale Pharmacogenomics Informs the Genetic Underpinnings of Simvastatin Use. Clin Pharmacol Ther 2021; 110:777-785. [PMID: 33837531 DOI: 10.1002/cpt.2260] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 04/01/2021] [Indexed: 12/31/2022]
Abstract
Studying drug-metabolizing enzymes, encoded by pharmacogenes, may inform biological mechanisms underlying the diseases for which a medication is prescribed. Until recently, pharmacogenes could not be studied at biobank scale. In 7,649 unrelated African-ancestry (AFR) and 326,214 unrelated European-ancestry (EUR) participants from the UK Biobank, we associated pharmacogene haplotypes from 50 genes with 265 (EUR) and 17 (AFR) medication use phenotypes using generalized linear models. In EUR, N-acetyltransferase 2 (NAT2) metabolizer phenotype and activity score were associated with simvastatin use. The dose of NAT2*1 was associated with simvastatin use when compared with NAT2*5 (the most common haplotype). This association was robust to effects of low-density lipoprotein cholesterol (LDL-C) concentration (NAT2*1 odds ratio (OR) = 1.07, 95% CI: 1.05-1.09, P = 1.14 × 10-8 ) and polygenic risk for LDL-C concentration (NAT2*1 OR = 1.09, 95% CI: 1.04-1.14, P = 2.26 × 10-4 ). Interactive effects between NAT2*1 and simvastatin use on LDL-C concentration (OR = 0.957, 95% CI: 0.916-0.998, P = 0.045) were replicated in the electronic Medical Records and Genomics Pharmacogenetic Sequencing Pilot (eMERGE-PGx) cohort (OR = 0.987, 95% CI: 0.976-0.998, P = 0.029). We used biobank-scale data to uncover and replicate an association between NAT2 locus variation and better response to statin therapy. Testing NAT2 alleles may be useful for making clinical decisions regarding the potential benefit (e.g., absolute risk reduction) in LDL-C concentration prior to statin treatment.
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Affiliation(s)
- Frank R Wendt
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Dora Koller
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Gita A Pathak
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Daniel Jacoby
- Section of Cardiovascular Diseases, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Edward J Miller
- Section of Cardiovascular Diseases, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
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Ji X, Ning B, Liu J, Roberts R, Lesko L, Tong W, Liu Z, Shi T. Towards population-specific pharmacogenomics in the era of next-generation sequencing. Drug Discov Today 2021; 26:1776-1783. [PMID: 33892143 DOI: 10.1016/j.drudis.2021.04.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 01/22/2021] [Accepted: 04/12/2021] [Indexed: 11/27/2022]
Abstract
Pharmacogenomics (PGx) has essential roles in identifying optimal drug responders, optimizing dosage regimens and avoiding adverse events. Population-specific therapeutic interventions that tackle the genetic root causes of clinical outcomes are an important precision medicine strategy. In this perspective, we discuss next-generation sequencing genotyping and its significance for population-specific PGx applications. We emphasize the potential of NGS for preemptive pharmacogenotyping, which is crucial to population-specific clinical studies and patient care. We also provide examples that use publicly available population-based genomics data for population-specific PGx studies. Last, we discuss the remaining challenges and regulatory efforts towards improvements in this field.
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Affiliation(s)
- Xiangjun Ji
- The Center for Bioinformatics and Computational Biology, The Institute of Biomedical Sciences and School of Life Sciences, School of Statistics, East China Normal University, Shanghai 200241, China; Guangdong Provincial Key Laboratory of Proteomics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Baitang Ning
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA
| | - Jinghua Liu
- Guangdong Provincial Key Laboratory of Proteomics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Ruth Roberts
- ApconiX, BioHub at Alderley Park, Alderley Edge SK10 4TG, UK; University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Larry Lesko
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, FL, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA.
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA.
| | - Tieliu Shi
- The Center for Bioinformatics and Computational Biology, The Institute of Biomedical Sciences and School of Life Sciences, School of Statistics, East China Normal University, Shanghai 200241, China; Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA; National Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
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Chan PA, Lewis KL, Biesecker BB, Erby LH, Fasaye GA, Epps S, Biesecker LG, Turbitt E. Preferences for and acceptability of receiving pharmacogenomic results by mail: A focus group study with a primarily African-American cohort. J Genet Couns 2021; 30:1582-1590. [PMID: 33876469 DOI: 10.1002/jgc4.1424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 03/18/2021] [Accepted: 03/20/2021] [Indexed: 01/12/2023]
Abstract
Although genetic counseling is traditionally done through in-person, one-on-one visits, workforce shortages call for efficient result return mechanisms. Studies have shown that telephone and in-person return of cancer genetic results are equivalent for patient outcomes. Few studies have been conducted with other modes, result types or racially diverse participants. This study explored participants' perspectives on receiving pharmacogenomic results by mail. Two experienced moderators facilitated six focus groups with 49 individuals who self-identified primarily as African-American and consented to participate in a genome sequencing cohort study. Participants were given a hypothetical pharmacogenomic result report (positive for c.521T>C in SLCO1B1). An accompanying letter explained that the result was associated with statin intolerance along with a recommendation to share it with one's doctor and immediate relatives. Participants reacted to the idea of receiving this type of result by mail, discussing whether the letter's information was sufficient and what they predicted they would do with the result. Two researchers coded the focus group transcripts and identified themes. Many participants thought that it was appropriate to receive the result through the mail, but some suggested a phone call alerting the recipient to the letter. Others emphasized that although a letter was acceptable for disclosing pharmacogenomic results, it would be insufficient for what they perceived as life-threatening results. Most participants found the content sufficient. Some participants suggested resources about statin intolerance and warning signs be added. Most claimed they would share the result with their doctor, yet few participants offered they would share the result with their relatives. This exploratory study advances the evidence that African-American research participants are receptive to return of certain genetic results by approaches that do not involve direct contact with a genetic counselor and intend to share results with providers. ClinSeq: A Large-Scale Medical Sequencing Clinical Research Pilot Study (NCT00410241).
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Affiliation(s)
- Priscilla A Chan
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | - Katie L Lewis
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | | | - Lori H Erby
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | | | - Sandra Epps
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | - Leslie G Biesecker
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | - Erin Turbitt
- University of Technology Sydney, Sydney, Australia
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Milo Rasouly H, Aggarwal V, Bier L, Goldstein DB, Gharavi AG. Cases in Precision Medicine: Genetic Testing to Predict Future Risk for Disease in a Healthy Patient. Ann Intern Med 2021; 174:540-547. [PMID: 33460345 DOI: 10.7326/m20-5713] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Genetic testing is performed more routinely in clinical practice, and direct-to-consumer tests are widely available. It has obvious appeal as a preventive health measure. Clinicians and their healthy patients increasingly inquire about genetic testing as a tool for predicting diseases, such as cancer, heart disease, or dementia. Despite demonstrated utility for diagnosis in the setting of many diseases, genetic testing still has many limitations as a predictive tool for healthy persons. This article uses a hypothetical case to review key considerations for predictive genetic testing.
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Affiliation(s)
- Hila Milo Rasouly
- Columbia University Irving Medical Center, New York, New York (H.M.R., A.G.G.)
| | - Vimla Aggarwal
- Hammer Health Sciences, New York, New York (V.A., L.B., D.B.G.)
| | - Louise Bier
- Hammer Health Sciences, New York, New York (V.A., L.B., D.B.G.)
| | | | - Ali G Gharavi
- Columbia University Irving Medical Center, New York, New York (H.M.R., A.G.G.)
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Patel JN, Boselli D, Jandrisevits EJ, Hamadeh IS, Salem A, Meadors P, Walsh D. Potentially actionable pharmacogenetic variants and symptom control medications in oncology. Support Care Cancer 2021; 29:5927-5934. [PMID: 33758969 DOI: 10.1007/s00520-021-06170-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 03/18/2021] [Indexed: 01/26/2023]
Abstract
PURPOSE We estimated the prevalence of potentially actionable pharmacogenetic (PGx) variants related to symptom control medications (SCMs) based on institutional prescribing patterns and correlated presenting symptoms with SCM prescribing. METHODS This was a retrospective study of adult ambulatory cancer patients undergoing electronic distress screening (EDS) within 90 days of intake to the cancer hospital. We estimated the proportion prescribed SCM(s) with PGx evidence within 90 days of intake. Those with potentially actionable variants were estimated using population frequency data from 1000 genomes. The expected number at risk of altered drug response was estimated. The associations between symptom scores and SCM(s) were estimated with logistic regression and threshold analyses performed with receiver operating characteristic (ROC) curves. RESULTS Of 6985 patients, 3222 (46%) received ≥ one SCM. Of these, 2760 (86%) received SCM(s) with PGx evidence for CYP2B6, CYP2C19, CYP2D6, or SLC6A4; 2719 (84%) received a drug metabolized by CYP2D6, most commonly hydrocodone (40.4%), ondansetron (35.6%), oxycodone (24.2%), and/or tramadol (7.1%). Based on this, about one quarter were expected to have altered metabolism and/or drug response. One third were prescribed two or more SCMs with PGx evidence. About half reported at least one severe symptom, which significantly correlated with SCM prescribing (p < 0.001). Threshold scores were identified that highly correlated with SCM prescribing for anxiety, depression, nausea, neuropathy, pain, and sleep. CONCLUSION About half presented with significant symptom burden, which highly correlated with SCM prescribing. Most received SCMs with PGx evidence. Preemptive PGx testing for these variants should be evaluated in prospective trials to evaluate the impact on symptom control.
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Affiliation(s)
- Jai N Patel
- Department of Cancer Pharmacology & Pharmacogenomics, Atrium Health Levine Cancer Institute, 1021 Morehead Medical Drive, Charlotte, NC, 28204, USA.
| | - Danielle Boselli
- Department of Biostatistics, Atrium Health Levine Cancer Institute, Charlotte, NC, USA
| | - Elizabeth J Jandrisevits
- Department of Cancer Pharmacology & Pharmacogenomics, Atrium Health Levine Cancer Institute, 1021 Morehead Medical Drive, Charlotte, NC, 28204, USA
| | - Issam S Hamadeh
- Department of Cancer Pharmacology & Pharmacogenomics, Atrium Health Levine Cancer Institute, 1021 Morehead Medical Drive, Charlotte, NC, 28204, USA
| | - Ahmed Salem
- Department of Cancer Pharmacology & Pharmacogenomics, Atrium Health Levine Cancer Institute, 1021 Morehead Medical Drive, Charlotte, NC, 28204, USA
| | - Patrick Meadors
- Section of Psycho-oncology, Center for Supportive Care and Survivorship, Atrium Health Levine Cancer Institute, Charlotte, NC, USA
| | - Declan Walsh
- Department of Supportive Oncology, Atrium Health Levine Cancer Institute, Charlotte, NC, USA
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Abstract
OBJECTIVES Pharmacogenomic testing (PGX) implementation is rapidly expanding, including pre-emptive testing funded by health systems. PGX continues to develop an evidence base that it saves money and improves clinical outcomes. Identifying the potential impact of pre-emptive testing in specific populations may aid in the development of a business case. METHODS We utilized a software tool that can evaluate patient drug lists and identified groups of patients most likely to benefit from implementation of a PGX testing program in a major medical system population. RESULTS Medication lists were obtained for sixteen patient groups with a total of 82 613 patients. The percent of patients in each group with testing 'Recommended', 'Strongly recommended', or 'Required' ranged from 12.7% in the outpatient pediatric psychiatry group to 75.7% in the any adult inpatient age >50 years group. Some of the highest yield drugs identified were citalopram, simvastatin, escitalopram, metoprolol, clopidogrel, tramadol, and ondansetron. CONCLUSION We demonstrate a significant number of patients in each group may have benefit, but targeting certain ones for pre-emptive testing may result in the initial highest yield for a health system.
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Yu MHC, Chan MCY, Chung CCY, Li AWT, Yip CYW, Mak CCY, Chau JFT, Lee M, Fung JLF, Tsang MHY, Chan JCK, Wong WHS, Yang J, Chui WCM, Chung PHY, Yang W, Lee SL, Chan GCF, Tam PKH, Lau YL, Tang CSM, Yeung KS, Chung BHY. Actionable pharmacogenetic variants in Hong Kong Chinese exome sequencing data and projected prescription impact in the Hong Kong population. PLoS Genet 2021; 17:e1009323. [PMID: 33600428 PMCID: PMC7891783 DOI: 10.1371/journal.pgen.1009323] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 12/30/2020] [Indexed: 12/11/2022] Open
Abstract
Preemptive pharmacogenetic testing has the potential to improve drug dosing by providing point-of-care patient genotype information. Nonetheless, its implementation in the Chinese population is limited by the lack of population-wide data. In this study, secondary analysis of exome sequencing data was conducted to study pharmacogenomics in 1116 Hong Kong Chinese. We aimed to identify the spectrum of actionable pharmacogenetic variants and rare, predicted deleterious variants that are potentially actionable in Hong Kong Chinese, and to estimate the proportion of dispensed drugs that may potentially benefit from genotype-guided prescription. The projected preemptive pharmacogenetic testing prescription impact was evaluated based on the patient prescription data of the public healthcare system in 2019, serving 7.5 million people. Twenty-nine actionable pharmacogenetic variants/ alleles were identified in our cohort. Nearly all (99.6%) subjects carried at least one actionable pharmacogenetic variant, whereas 93.5% of subjects harbored at least one rare deleterious pharmacogenetic variant. Based on the prescription data in 2019, 13.4% of the Hong Kong population was prescribed with drugs with pharmacogenetic clinical practice guideline recommendations. The total expenditure on actionable drugs was 33,520,000 USD, and it was estimated that 8,219,000 USD (24.5%) worth of drugs were prescribed to patients with an implicated actionable phenotype. Secondary use of exome sequencing data for pharmacogenetic analysis is feasible, and preemptive pharmacogenetic testing has the potential to support prescription decisions in the Hong Kong Chinese population. Pharmacogenetic testing provides relevant drug phenotype information to guide personalized drug prescription, which potentially improves drug efficacy and prevent adverse drug reactions. However, its implementation in the Chinese population is limited by the lack of Chinese-specific pharmacogenetics data. In this study, we studied the spectrum of 133 actionable pharmacogenetic variants and rare deleterious variants in 108 pharmacogenes using an exome sequencing consisting of 1116 Hong Kong Chinese subjects. It was found that nearly all individuals carried at least one actionable pharmacogenetic variant and one rare, predicted deleterious pharmacogenetic variant. In addition, we projected the potential prescription impact of actionable pharmacogenetic variants using prescription data of the Hong Kong's public healthcare system. We estimated that one-seventh of the Hong Kong population received at least one of the 36 drugs with clinical pharmacogenetics guideline recommendations. The findings demonstrated the potential of pharmacogenetic testing in improving patient care and resource allocation in Chinese. The cohort dataset also supports clinical implementation of pharmacogenetics in the Chinese population.
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Affiliation(s)
- Mullin Ho Chung Yu
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Marcus Chun Yin Chan
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Claudia Ching Yan Chung
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Andrew Wang Tat Li
- Department of Pharmacy, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
| | - Chara Yin Wa Yip
- Department of Pharmacy, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
| | - Christopher Chun Yu Mak
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Jeffrey Fong Ting Chau
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Mianne Lee
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Jasmine Lee Fong Fung
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Mandy Ho Yin Tsang
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Joshua Chun Ki Chan
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Wilfred Hing Sang Wong
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Jing Yang
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | | | - Patrick Ho Yu Chung
- Department of Surgery, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Wanling Yang
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - So Lun Lee
- Department of Paediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
| | - Godfrey Chi Fung Chan
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, The Hong Kong Children’s Hospital, Kowloon Bay, Hong Kong SAR, China
| | - Paul Kwong Hang Tam
- Department of Surgery, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Dr Li Dak-Sum Research Centre, The University of Hong Kong–Karolinska Institutet Collaboration in Regenerative Medicine, Pokfulam, Hong Kong SAR, China
| | - Yu Lung Lau
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, The Hong Kong Children’s Hospital, Kowloon Bay, Hong Kong SAR, China
| | - Clara Sze Man Tang
- Department of Surgery, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Dr Li Dak-Sum Research Centre, The University of Hong Kong–Karolinska Institutet Collaboration in Regenerative Medicine, Pokfulam, Hong Kong SAR, China
- * E-mail: (CSMT); (KSY); (BHYC)
| | - Kit San Yeung
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- * E-mail: (CSMT); (KSY); (BHYC)
| | - Brian Hon Yin Chung
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, The Hong Kong Children’s Hospital, Kowloon Bay, Hong Kong SAR, China
- * E-mail: (CSMT); (KSY); (BHYC)
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Fan M, Yarema MC, Box A, Hume S, Aitchison KJ, Bousman CA. Identification of high-impact gene-drug pairs for pharmacogenetic testing in Alberta, Canada. Pharmacogenet Genomics 2021; 31:29-39. [PMID: 32826605 DOI: 10.1097/fpc.0000000000000418] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVES To facilitate decision-making and priority-setting related to Alberta's Pharmacogenomics (PGx) testing implementation strategy by identifying gene-drug pairs with the highest potential impact on prescribing practices in Alberta. PATIENTS AND METHODS Annual drug dispensing data for Alberta from 2012 to 2016 for 57 medications with PGx-based prescribing guidelines were obtained, along with population estimates and demographics (age and ethnicity). Frequencies of actionable PGx genotypes by ethnicity were obtained from the Pharmacogenomics Knowledgebase (PharmGKB). Annual dispensing activity for each of the 57 medications was calculated for the full population (all ages) and children/youth (0-19 years). Alberta ethnicity data were cross-referenced with genetic frequency data for each of the main ethnic groups from PharmGKB to estimate the proportion of individuals with actionable genotypes. Actionable genotype proportions and drug dispensing frequencies were collectively used to identify high impact gene-drug pairs. RESULTS We found (a) half of the drugs with PGx-based prescribing guidelines, namely, analgesics, proton pump inhibitors, psychotropics, and cardiovascular drugs, were dispensed at high frequencies (>1% of the entire population), (b) the dispensing rate for about one-third of these drugs increased over the 5-year study period, (c) between 1.1 and 45% of recipients of these drugs carried actionable genotypes, and (d) the gene-drug pairs with greatest impact in Alberta predominatly included CYP2C19 or CYP2D6. CONCLUSIONS We uncovered specific patterns in drug dispensing and identified important gene-drug pairs that will inform the planning and development of an evidenced-based PGx testing service in Alberta, Canada. Adaptation of our approach may facilitate the process of evidence-based PGx testing implementation in other jurisdictions.
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Affiliation(s)
- Mikayla Fan
- Biomedical Sciences, Cumming School of Medicine, University of Calgary, Calgary
| | - Mark C Yarema
- Poison and Drug Information Service, Alberta Health Services, Calgary
- Section of Clinical Pharmacology and Toxicology, Alberta Health Services, Calgary
- Department of Emergency Medicine, University of Calgary, Calgary
| | - Adrian Box
- Alberta Precision Laboratories, Alberta Health Services, Edmonton
- Department of Pathology and Laboratory Medicine, University of Calgary, Calgary
| | - Stacey Hume
- Alberta Precision Laboratories, Alberta Health Services, Edmonton
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton
| | - Katherine J Aitchison
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton
- Department of Psychiatry and Medical Genetics, University of Alberta, Edmonton
| | - Chad A Bousman
- Department of Medical Genetics, Psychiatry, Physiology and Pharmacology, University of Calgary, Calgary
- Alberta Children's Hospital Research Institute, Calgary
- Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
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71
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Qin W, Du Z, Xiao J, Duan H, Shu Q, Li H. Evaluation of clinical impact of pharmacogenomics knowledge involved in CPIC guidelines on Chinese pediatric patients. Pharmacogenomics 2021; 21:209-219. [PMID: 31967514 DOI: 10.2217/pgs-2019-0153] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Aim: To evaluate the clinical benefits of implementing pharmacogenomics testing for Chinese pediatric patients. Materials & methods : Based on the drug-gene interactions involved in the Clinical Pharmacogenetics Implementation Consortium guidelines, whole-genome sequencing data from the Chinese Academy of Sciences Precision Medicine Initiative project and the medication data of pediatric patients from a children's hospital, the prevalence of the Chinese population with actionable pharmacogenomic variants was calculated, the prescribing pattern for pediatric patients was analyzed. Results: 37.0% of the drugs involved in the Clinical Pharmacogenetics Implementation Consortium guidelines were used by Chinese pediatric patients, 8.91% inpatients and 0.89% outpatients received at least one pharmacogenomics medication, 1.24% (4803) inpatients and 0.16% (2940) outpatients were estimated to be at high risk of pharmacogenomic-related adverse therapeutic outcomes. Conclusion: Implementing pharmacogenomics testing can improve therapeutic outcomes for many Chinese pediatric patients.
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Affiliation(s)
- Weifeng Qin
- The Children's Hospital, Zhejiang University School of Medicine and National Clinical Research Center for Child Health, Hangzhou 310052, PR China.,College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Zhenglin Du
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, PR China
| | - Jingfa Xiao
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, PR China
| | - Huilong Duan
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Qiang Shu
- The Children's Hospital, Zhejiang University School of Medicine and National Clinical Research Center for Child Health, Hangzhou 310052, PR China
| | - Haomin Li
- The Children's Hospital, Zhejiang University School of Medicine and National Clinical Research Center for Child Health, Hangzhou 310052, PR China
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72
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Patients dispensed medications with actionable pharmacogenomic biomarkers: rates and characteristics. Genet Med 2021; 23:782-786. [PMID: 33420348 PMCID: PMC9067543 DOI: 10.1038/s41436-020-01044-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 11/11/2020] [Accepted: 11/12/2020] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Pharmacogenomic biomarkers are increasingly listed on medication labels and authoritative guidelines but pharmacogenomic-guided prescribing is not yet common. Our objective was to assess the potential for incorporating knowledge of patients' genomic characteristics into prescribing practices. METHODS We performed a retrospective analysis of claims data for 2,096,971 beneficiaries with pharmacy coverage from a national, commercial health insurance plan between January 2017 and December 2019. Children between 0 and 17 years comprised 21% of the cohort. Adults were age 18 to 64. Medications with actionable pharmacogenomic biomarkers (MAPBs) were identified using public information from the US Food and Drug Administration (FDA), Clinical Pharmacogenomics Implementation Consortium (CPIC), and PharmGKB. RESULTS MAPBs were dispensed to 63% of the adults and 29% of the children in the cohort. Most frequently dispensed were ibuprofen, ondansetron, codeine, and oxycodone. Most common were medications with CYP2D6, G6PD, or CYPC19 pharmacogenomic biomarkers. Ten percent of the cohort were codispensed more than one MAPB for at least 30 days. CONCLUSION The number of people who might benefit from pharmacogenomic-guided prescribing is substantial. Future work should address obstacles to integrating genomic data into prescriber workflows, complex factors contributing to the magnitude of benefit, and the clinical availability of reliable on-demand or pre-emptive pharmacogenomic testing.
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73
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Dong OM, Bates J, Chanfreau-Coffinier C, Naglich M, Kelley MJ, Meyer LJ, Icardi M, Vassy JL, Sriram P, Heise CW, Rivas S, Ribeiro M, Jacobitz R, Rozelle S, Chapman JG, Voora D. Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program. Pharmacogenomics 2021; 22:137-144. [PMID: 33403869 DOI: 10.2217/pgs-2020-0173] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
In 2019, the Veterans Affairs (VA), the largest integrated US healthcare system, started the Pharmacogenomic Testing for Veterans (PHASER) clinical program that provides multi-gene pharmacogenomic (PGx) testing for up to 250,000 veterans at approximately 50 sites. PHASER is staggering program initiation at sites over a 5-year period from 2019 to 2023, as opposed to simultaneous initiation at all sites, to facilitate iterative program quality improvements through Plan-Do-Study-Act cycles. Current resources in the PGx field have not focused on multisite, remote implementation of panel-based PGx testing. In addition to bringing large scale PGx testing to veterans, the PHASER program is developing a roadmap to maximize uptake and optimize the use of PGx to improve drug response outcomes.
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Affiliation(s)
- Olivia M Dong
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
| | - Jill Bates
- Durham VA Health Care System, Durham, NC 27705, USA.,Division of Practice Advancement & Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - Michael Naglich
- Institute for Medical Research, Durham VA Medical Center, Durham, NC 27705, USA
| | - Michael J Kelley
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke University Medical Center, Durham, NC 27708, USA.,Department of Veterans Affairs, National Oncology Program Office, Office of Specialty Care, Durham, NC 27705, USA
| | - Laurence J Meyer
- Department of Veterans Affairs, Washington, DC 20571, USA.,Department of Dermatology, University of Utah, UT 84112, USA
| | - Michael Icardi
- Department of Veterans Affairs, Washington, DC 20571, USA
| | - Jason L Vassy
- VA Boston Healthcare System, Boston, MA 02130, USA.,Harvard Medical School, Boston, MA 02115, USA
| | - Peruvemba Sriram
- North Florida/South Georgia Veterans Health System, Gainesville, FL 32608, USA
| | - Craig William Heise
- Phoenix VA Health Care System, Phoenix, AZ 85012, USA.,The University of Arizona College of Medicine - Phoenix, Phoenix, AZ 85004, USA
| | | | - Maria Ribeiro
- Atlanta VA Medical Center, Atlanta, GA 30033, USA.,Department of Hematology & Medical Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Russell Jacobitz
- North Florida/South Georgia Veterans Health System, Gainesville, FL 32608, USA
| | - Susan Rozelle
- North Florida/South Georgia Veterans Health System, Gainesville, FL 32608, USA
| | - Jennifer G Chapman
- Institute for Medical Research, Durham VA Medical Center, Durham, NC 27705, USA
| | - Deepak Voora
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
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74
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Češková E, Šilhán P. From Personalized Medicine to Precision Psychiatry? Neuropsychiatr Dis Treat 2021; 17:3663-3668. [PMID: 34934319 PMCID: PMC8684413 DOI: 10.2147/ndt.s337814] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 11/16/2021] [Indexed: 12/28/2022] Open
Abstract
Personalised medicine aims to find an individualized approach for each particular patient. Most factors used in current psychiatry, however, depend on the assessment made by the individual clinician and lack a higher degree of reliability. Precision medicine bases decisions on quantifiable indicators available thanks to the tremendous progress in science and technology facilitating the acquisition, processing and analysis of huge amounts of data. So far, psychiatry has not been benefiting enough from the advanced diagnostic technologies; nevertheless, we are witnessing the dawn of the era of precision psychiatry, starting with the gathering of sufficient amounts of data and its analysis by the means of artificial intelligence and machine learning. First results of this approach in psychiatry are available, which facilitate diagnosis assessment, course prediction, and appropriate treatment choice. These processes are often so complex and difficult to understand that they may resemble a "black box", which can slow down the acceptance of the results of this approach in clinical practice. Still, bringing precision medicine including psychiatry to standard clinical practice is a big challenge that can result in a completely new and transformative concept of health care. Such extensive changes naturally have both their supporters and opponents. This paper aims to familiarize clinically oriented physicians with precision psychiatry and to attract their attention to its recent developments. We cover the theoretical basis of precision medicine, its specifics in psychiatry, and provide examples of its use in the field of diagnostic assessment, course prediction, and appropriate treatment planning.
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Affiliation(s)
- Eva Češková
- Department of Psychiatry, University Hospital Ostrava, Ostrava, Czech Republic.,Department of Clinical Neurosciences, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic.,Department of Psychiatry, University Hospital Brno, Brno, Czech Republic.,Department of Psychiatry, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Petr Šilhán
- Department of Psychiatry, University Hospital Ostrava, Ostrava, Czech Republic.,Department of Clinical Neurosciences, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
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75
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Stevenson JM, Alexander GC, Palamuttam N, Mehta HB. Projected Utility of Pharmacogenomic Testing Among Individuals Hospitalized With COVID-19: A Retrospective Multicenter Study in the United States. Clin Transl Sci 2021; 14:153-162. [PMID: 33085221 PMCID: PMC7877860 DOI: 10.1111/cts.12919] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 10/07/2020] [Indexed: 12/24/2022] Open
Abstract
Many academic institutions are collecting blood samples from patients seeking treatment for coronavirus disease 2019 (COVID-19) to build research biorepositories. It may be feasible to extract pharmacogenomic (PGx) information from biorepositories for clinical use. We sought to characterize the potential value of multigene PGx testing among individuals hospitalized with COVID-19 in the United States. We performed a cross-sectional analysis of electronic health records from consecutive individuals hospitalized with COVID-19 at a large, urban academic health system. We characterized medication orders, focusing on medications with actionable PGx guidance related to 14 commonly assayed genes (CYP2C19, CYP2C9, CYP2D6, CYP3A5, DPYD, G6PD, HLA-A, HLA-B, IFNL3, NUDT15, SLCO1B1, TPMT, UGT1A1, and VKORC1). A simulation analysis combined medication data with population phenotype frequencies to estimate how many treatment modifications would be enabled if multigene PGx results were available. Sixty-four unique medications with PGx guidance were ordered at least once in the cohort (n = 1,852, mean age 60.1 years). Nearly nine in 10 individuals (89.7%) had at least one order for a medication with PGx guidance and 427 patients (23.1%) had orders for 4 or more actionable medications. Using a simulation, we estimated that 17 treatment modifications per 100 patients would be enabled if PGx results were available. The genes CYP2D6 and CYP2C19 were responsible for the majority of treatment modifications, and the medications most often affected were ondansetron, oxycodone, and clopidogrel. PGx results would be relevant for nearly all individuals hospitalized with COVID-19 and would provide the opportunity to improve clinical care.
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Affiliation(s)
- James M. Stevenson
- Division of Clinical PharmacologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - G. Caleb Alexander
- Center for Drug Safety and EffectivenessJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Division of General Internal MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Natasha Palamuttam
- Division of Health Sciences InformaticsJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Hemalkumar B. Mehta
- Center for Drug Safety and EffectivenessJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
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76
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Roberts TA, Wagner JA, Sandritter T, Black BT, Gaedigk A, Stancil SL. Retrospective Review of Pharmacogenetic Testing at an Academic Children's Hospital. Clin Transl Sci 2021; 14:412-421. [PMID: 33048453 PMCID: PMC7877836 DOI: 10.1111/cts.12895] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 09/02/2020] [Indexed: 12/28/2022] Open
Abstract
There is limited evidence to support pharmacogenetic (PGx) testing in children. We conducted a retrospective review of PGx testing among 452 patients at an academic children's hospital to determine the potential utility of PGx in diseases of childhood and to identify targets for future pediatric pharmacogenetic research. An actionable gene-drug pair associated with the 28 genes tested (Clinical Pharmacogenetics Implementation Consortium (CPIC) level A or B, Pharmacogenomics Knowledge Base (PharmGKB) level 1A or B, or US Food and Drug Administration (FDA) recommendation and a PharmGKB level) was present in 98.7% of patients. We identified 203 actionable gene-drug-diagnosis groups based on the indications for each actionable drug listed in Lexicomp. Among patients with an actionable gene-drug-diagnosis group, 49.3% had a diagnosis where the drug was a therapeutic option and PGx could be used to guide treatment selection. Among patients with an associated diagnosis, 30.9% had a prescription for the actionable drug allowing PGx guided dosing. Three genes (CYP2C19, CYP2D6, and CYP3A5) accounted for all the gene-drug-diagnosis groups with matching diagnoses and prescriptions. The most common gene-drug-diagnosis groups with matching diagnoses and prescriptions were CYP2C19-citalopram-escitalopram-depression 3.3% of patients tested; CYP2C19-dexlansoprazole-gastritis-esophagitis 3.1%; CYP2C19-omeprazole-gastritis-esophagitis 2.4%; CYP2D6-atomoxetine-attention deficit hyperactivity disorder 2.2%; and CYP2C19-citalopram-escitalopram-obsessive-compulsive disorder 1.5%. PGx could be used to guide selection of current treatment options or medication dosing in almost half (48.7%) of pediatric patients tested. Mood disorders and gastritis/esophagitis are promising targets for future study of PGx testing because of the high prevalence of these diagnoses and associated actionable gene-drug pairs in the pediatric population.
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Affiliation(s)
- Timothy A. Roberts
- Division of Adolescent MedicineChildren’s Mercy Kansas CityKansas CityMissouriUSA
- Department of PediatricsUMKC School of MedicineKansas CityMissouriUSA
| | - Jennifer A. Wagner
- Department of PediatricsUMKC School of MedicineKansas CityMissouriUSA
- Division of Clinical PharmacologyToxicology, and Therapeutic InnovationChildren’s Mercy Kansas CityKansas CityMissouriUSA
| | - Tracy Sandritter
- Division of Clinical PharmacologyToxicology, and Therapeutic InnovationChildren’s Mercy Kansas CityKansas CityMissouriUSA
| | - Benjamin T. Black
- Department of PediatricsUMKC School of MedicineKansas CityMissouriUSA
- Division of Developmental and Behavioral HealthChildren’s Mercy Kansas CityKansas CityMissouriUSA
| | - Andrea Gaedigk
- Department of PediatricsUMKC School of MedicineKansas CityMissouriUSA
- Division of Clinical PharmacologyToxicology, and Therapeutic InnovationChildren’s Mercy Kansas CityKansas CityMissouriUSA
| | - Stephani L. Stancil
- Division of Adolescent MedicineChildren’s Mercy Kansas CityKansas CityMissouriUSA
- Division of Clinical PharmacologyToxicology, and Therapeutic InnovationChildren’s Mercy Kansas CityKansas CityMissouriUSA
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Vassy JL, Gaziano JM, Green RC, Ferguson RE, Advani S, Miller SJ, Chun S, Hage AK, Seo SJ, Majahalme N, MacMullen L, Zimolzak AJ, Brunette CA. Effect of Pharmacogenetic Testing for Statin Myopathy Risk vs Usual Care on Blood Cholesterol: A Randomized Clinical Trial. JAMA Netw Open 2020; 3:e2027092. [PMID: 33270123 PMCID: PMC7716196 DOI: 10.1001/jamanetworkopen.2020.27092] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
IMPORTANCE Nonadherence to statin guidelines is common. The solute carrier organic anion transporter family member 1B1 (SLCO1B1) genotype is associated with simvastatin myopathy risk and is proposed for clinical implementation. The unintended harms of using pharmacogenetic information to guide pharmacotherapy remain a concern for some stakeholders. OBJECTIVE To determine the impact of delivering SLCO1B1 pharmacogenetic results to physicians on the effectiveness of atherosclerotic cardiovascular disease (ASCVD) prevention (measured by low-density lipoprotein cholesterol [LDL-C] levels) and concordance with prescribing guidelines for statin safety and effectiveness. DESIGN, SETTING, AND PARTICIPANTS This randomized clinical trial was performed from December 2015 to July 2019 at 8 primary care practices in the Veterans Affairs Boston Healthcare System. Participants included statin-naive patients with elevated ASCVD risk. Data analysis was performed from October 2019 to September 2020. INTERVENTIONS SLCO1B1 genotyping and results reporting to primary care physicians at baseline (intervention group) vs after 1 year (control group). MAIN OUTCOMES AND MEASURES The primary outcome was the 1-year change in LDL-C level. The secondary outcomes were 1-year concordance with American College of Cardiology-American Heart Association and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for statin therapy and statin-associated muscle symptoms (SAMS). RESULTS Among 408 patients (mean [SD] age, 64.1 [7.8] years; 25 women [6.1%]), 193 were randomized to the intervention group and 215 were randomized to the control group. Overall, 120 participants (29%) had a SLCO1B1 genotype indicating increased simvastatin myopathy risk. Physicians offered statin therapy to 65 participants (33.7%) in the intervention group and 69 participants (32.1%) in the control group. Compared with patients whose physicians did not know their SLCO1B1 results at baseline, patients whose physicians received the results had noninferior reductions in LDL-C at 12 months (mean [SE] change in LDL-C, -1.1 [1.2] mg/dL in the intervention group and -2.2 [1.3] mg/dL in the control group; difference, -1.1 mg/dL; 90% CI, -4.1 to 1.8 mg/dL; P < .001 for noninferiority margin of 10 mg/dL). The proportion of patients with American College of Cardiology-American Heart Association guideline-concordant statin prescriptions in the intervention group was noninferior to that in the control group (12 patients [6.2%] vs 14 patients [6.5%]; difference, -0.003; 90% CI, -0.038 to 0.032; P < .001 for noninferiority margin of 15%). All patients in both groups were concordant with CPIC guidelines for safe statin prescribing. Physicians documented 2 and 3 cases of SAMS in the intervention and control groups, respectively, none of which was associated with a CPIC guideline-discordant prescription. Among patients with a decreased or poor SLCO1B1 transporter function genotype, simvastatin was prescribed to 1 patient in the control group but none in the intervention group. CONCLUSIONS AND RELEVANCE Clinical testing and reporting of SLCO1B1 results for statin myopathy risk did not result in poorer ASCVD prevention in a routine primary care setting and may have been associated with physicians avoiding simvastatin prescriptions for patients at genetic risk for SAMS. Such an absence of harm should reassure stakeholders contemplating the clinical use of available pharmacogenetic results. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02871934.
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Affiliation(s)
- Jason L. Vassy
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Ariadne Labs, Boston, Massachusetts
| | - J. Michael Gaziano
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Robert C. Green
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Ariadne Labs, Boston, Massachusetts
| | - Ryan E. Ferguson
- VA Boston Healthcare System, Boston, Massachusetts
- Department of General Internal Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | | | | | - Sojeong Chun
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | - Anthony K. Hage
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | - Soo-Ji Seo
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | | | | | - Andrew J. Zimolzak
- VA Boston Healthcare System, Boston, Massachusetts
- Baylor College of Medicine, Houston, Texas
- Michael E. DeBakey VA Medical Center, Houston, Texas
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78
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Ramsey LB, Ong HH, Schildcrout JS, Shi Y, Tang LA, Hicks JK, El Rouby N, Cavallari LH, Tuteja S, Aquilante CL, Beitelshees AL, Lemkin DL, Blake KV, Williams H, Cimino JJ, Davis BH, Limdi NA, Empey PE, Horvat CM, Kao DP, Lipori GP, Rosenman MB, Skaar TC, Teal E, Winterstein AG, Owusu Obeng A, Salyakina D, Gupta A, Gruber J, McCafferty-Fernandez J, Bishop JR, Rivers Z, Benner A, Tamraz B, Long-Boyle J, Peterson JF, Van Driest SL. Prescribing Prevalence of Medications With Potential Genotype-Guided Dosing in Pediatric Patients. JAMA Netw Open 2020; 3:e2029411. [PMID: 33315113 PMCID: PMC7737091 DOI: 10.1001/jamanetworkopen.2020.29411] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 09/28/2020] [Indexed: 12/17/2022] Open
Abstract
Importance Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation. Objective To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions. Design, Setting, and Participants This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020. Exposures Prescription of 38 level A medications based on electronic health records. Main Outcomes and Measures Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally. Results Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes. Conclusions and Relevance These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.
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Affiliation(s)
- Laura B. Ramsey
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio
- Divisions of Research in Patient Services and Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
| | - Henry H. Ong
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Yaping Shi
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Leigh Anne Tang
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - J. Kevin Hicks
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Nihal El Rouby
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville
- James Winkle College of Pharmacy, University of Cincinnati, Cincinnati, Ohio
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville
| | - Sony Tuteja
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | | | | - Daniel L. Lemkin
- Department of Emergency Medicine, University of Maryland, Baltimore
| | - Kathryn V. Blake
- Center for Pharmacogenomics and Translational Research, Nemours Children’s Health System, Jacksonville, Florida
| | - Helen Williams
- Nemours Research Institute, Nemours Children’s Health System, Jacksonville, Florida
| | | | | | - Nita A. Limdi
- Department of Neurology, University of Alabama at Birmingham
| | - Philip E. Empey
- Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Christopher M. Horvat
- Department of Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - David P. Kao
- Department of Medicine, School of Medicine, University of Colorado, Aurora
| | - Gloria P. Lipori
- University of Florida Health and University of Florida Health Sciences Center, Gainesville
| | - Marc B. Rosenman
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis
- Department of Pediatrics, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois
| | - Todd C. Skaar
- Department of Medicine, Indiana University School of Medicine, Indianapolis
| | | | - Almut G. Winterstein
- Department of Pharmaceutical Outcomes and Policy and Center for Drug Evaluation and Safety, University of Florida, Gainesville
| | - Aniwaa Owusu Obeng
- The Charles Bronfman Institute for Personalized Medicine, Departments of Medicine and Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Daria Salyakina
- Personalized Medicine Initiative, Nicklaus Children’s Health System, Miami, Florida
| | - Apeksha Gupta
- Personalized Medicine Initiative, Nicklaus Children’s Health System, Miami, Florida
| | - Joshua Gruber
- Personalized Medicine Initiative, Nicklaus Children’s Health System, Miami, Florida
| | | | - Jeffrey R. Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis
| | - Zach Rivers
- Department of Pharmaceutical Care and Health Systems, University of Minnesota College of Pharmacy, Minneapolis
| | - Ashley Benner
- Clinical and Translational Science Institute, University of Minnesota, Minneapolis
| | - Bani Tamraz
- School of Pharmacy, University of California, San Francisco
| | | | - Josh F. Peterson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee
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79
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Nguyen TT, Pearson RA, Mohamed ME, Schladt DP, Berglund D, Rivers Z, Skaar DJ, Wu B, Guan W, van Setten J, Keating BJ, Dorr C, Remmel RP, Matas AJ, Mannon RB, Israni AK, Oetting WS, Jacobson PA. Pharmacogenomics in kidney transplant recipients and potential for integration into practice. J Clin Pharm Ther 2020; 45:1457-1465. [PMID: 32662547 PMCID: PMC7719579 DOI: 10.1111/jcpt.13223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 05/14/2020] [Accepted: 06/11/2020] [Indexed: 11/29/2022]
Abstract
WHAT IS KNOWN AND OBJECTIVE Pharmacogenomic biomarkers are now used in many clinical care settings and represent one of the successes of precision medicine. Genetic variants are associated with pharmacokinetic and pharmacodynamic changes leading to medication adverse effects and changes in clinical response. Actionable pharmacogenomic variants are common in transplant recipients and have implications for medications used in transplant, but yet are not broadly incorporated into practice. METHODS From the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group guidelines, and PharmGKB databases, 12 pharmacogenomic genes with 30 variants were selected and used to create diplotypes and actionable pharmacogenomic phenotypes. A total of 853 kidney allograft recipients who had genomic information available from a genome-wide association study were included. RESULTS Each recipient had at least one actionable pharmacogenomic diplotype/phenotype, whereas the majority (58%) had three or four actionable diplotypes/phenotypes and 17.4% had five or more among the 12 genes. The participants carried actionable diplotypes/phenotypes for multiple medications, including tacrolimus, azathioprine, clopidogrel, warfarin, simvastatin, voriconazole, antidepressants and proton-pump inhibitors. WHAT IS NEW AND CONCLUSION Pharmacogenomic variants are common in transplant recipients, and transplant recipients receive medications that have actionable variants. CLINICAL TRIAL Genomics of Transplantation, clinicaltrials.gov (NCT01714440).
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Affiliation(s)
- Tam T Nguyen
- College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | | | - Moataz E Mohamed
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
- Department of Pharmacy Practice, Faculty of Pharmacy, Helwan University, Cairo, Egypt
| | - David P Schladt
- Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, MN, USA
| | - Danielle Berglund
- Complex Care Core Analytics, Fairview University of Minnesota, Minneapolis, MN, USA
| | - Zachary Rivers
- Social and Administrative Pharmacy, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Debra J Skaar
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Baolin Wu
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Jessica van Setten
- Department of Cardiology, University Medical Center Utrecht, University of Utrecht, Utrecht, Netherlands
| | - Brendan J Keating
- Penn Transplant Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Casey Dorr
- Minneapolis Medical Research Foundation and Division of Nephrology, Hennepin Healthcare, Minneapolis, MN, USA
| | - Rory P Remmel
- Department of Medicinal Chemistry, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Arthur J Matas
- Department of Surgery, School of Medicine, University of Minnesota, Minneapolis, MN, USA
| | - Roslyn B Mannon
- Department of Nephrology, School of Medicine, University of Nebraska, Omaha, NE, USA
| | - Ajay K Israni
- Division of Nephrology, Hennepin Healthcare, Minneapolis, MN, USA
- Epidemiology & Community Health, University of Minnesota, Minneapolis, MN, USA
| | - William S Oetting
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Pamala A Jacobson
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
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80
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Knowledge, Attitudes, and Perceived Barriers toward Genetic Testing and Pharmacogenomics among Healthcare Workers in the United Arab Emirates: A Cross-Sectional Study. J Pers Med 2020; 10:jpm10040216. [PMID: 33182317 PMCID: PMC7711841 DOI: 10.3390/jpm10040216] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 10/27/2020] [Accepted: 11/05/2020] [Indexed: 02/05/2023] Open
Abstract
In order to successfully translate the scientific models of genetic testing and pharmacogenomics into clinical practice, empowering healthcare workers with the right knowledge and functional understanding on the subject is essential. Limited research in the United Arab Emirates (UAE) have assessed healthcare worker stances towards genomics. This study aimed to assess healthcare workers’ knowledge and attitudes on genetic testing. A cross-sectional study was conducted among healthcare workers practicing in either public or private hospitals or clinics as pharmacists, nurses, physicians, managers, and allied health. Participants were recruited randomly and via snowball techniques. Surveys were collected between April and September 2019; out of 552 respondents, 63.4% were female, the mean age was 38 (±9.6) years old. The mean knowledge score was 5.2 (±2.3) out of nine, which shows a fair level of knowledge. The scores of respondents of pharmacy were 5.1 (±2.5), medicine 6.0 (±2.0), and nursing 4.8 (±2.1). All participants exhibited a fair knowledge level about genetic testing and pharmacogenomics. Of the respondents, 91.9% showed a positive attitude regarding availability of genetic testing. The top identified barrier to implementation was the cost of testing (62%), followed by lack of training or education and insurance coverage (57.8% and 57.2%, respectively). Building upon the positive attitudes and tackling the barriers and challenges will pave the road for full implementation of genetic testing and pharmacogenomics in the UAE. We recommend empowering healthcare workers by improving needed and tailored competencies related to their area of practice. We strongly urge the stakeholders to streamline and benchmark the workflow, algorithm, and guidelines to standardize the health and electronic system. Lastly, we advocate utilizing technology and electronic decision support as well as the translational report to back up healthcare workers in the UAE.
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81
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Vernaz N, Simona A, Samer CF. The Swiss Cheese Prescribing Model for Precision Medicine. Am J Med 2020; 133:1249-1251. [PMID: 32603792 DOI: 10.1016/j.amjmed.2020.06.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 06/12/2020] [Accepted: 06/18/2020] [Indexed: 10/24/2022]
Affiliation(s)
- Nathalie Vernaz
- Medical Directorate, Finance Directorate Geneva University Hospitals, University of Geneva, Switzerland.
| | - Aurélien Simona
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals, University of Geneva, Switzerland
| | - Caroline Flora Samer
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals, University of Geneva, Switzerland
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82
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83
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Boyle J, Stock CJ. CYP2D6 Expression in Veterans Experiencing Opioid Overdose: A Postmortem Review. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2020; 13:289-293. [PMID: 32848444 PMCID: PMC7429207 DOI: 10.2147/pgpm.s261424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 07/20/2020] [Indexed: 12/20/2022]
Abstract
Purpose The purpose is to characterize the CYP2D6 genotype and predict the phenotype of decedents of opioid overdose to determine if the ultrarapid (UM) phenotype is over-represented in opioid overdose deaths. CYP2D6 is the enzyme responsible for metabolism of various opioids implicated in overdose. The UM group may be at greater risk for overdose due to the rapid metabolism of hydrocodone, oxycodone, or tramadol to more active/potent metabolites than their peers with (poor) PM, (intermediate) IM, or (extensive) EM metabolic phenotypes. Patients and Methods Blood samples obtained during autopsy following an opioid overdose from 75 US military veteran decedents prescribed hydrocodone, oxycodone, or tramadol from one VA medical center were analyzed. DNA extraction, CYP2D6 genotyping, and copy number variation (CNV) testing were performed using the iPLEX® genotyping assay and MassARRAY. Phenotype prediction was based on Clinical Pharmacogenetics Implementation Consortium (CPIC) recommendations. Toxicology results were obtained from Medical Examiner reports of the deceased. Prescription medication information was extracted from archived medical records. Results The majority of the sample had a phenotype of EM metabolizer (75%), with 7% of the total sample having a UM metabolizer phenotype. In addition to hydrocodone, oxycodone, and tramadol (found in 41% of opioid positive samples), other opioids found in toxicology tests included diacetylmorphine, fentanyl, buprenorphine, and methadone. Two or more substances, including alcohol, benzodiazepines, and other potentially sedating medications, were found in nearly half of the opioid positive toxicology samples. Conclusion In this study, 7% of veteran decedents of opioid overdose had CYP2D6 UM metabolic phenotype. The small sample size precludes a conclusion that the frequency of UM phenotype is greater than expected in North American Caucasian groups. The findings in this study do not support the hypothesis that the UM phenotype is over-represented in opioid overdose.
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Affiliation(s)
- Julia Boyle
- Department of Pharmacy, VA Salt Lake City Health Care System, Salt Lake City, UT, USA.,Department of Pharmacy Practice, Idaho State University College of Pharmacy, Meridian, ID, USA
| | - Christopher J Stock
- Department of Pharmacy, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
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84
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Scott SA, Scott ER, Seki Y, Chen AJ, Wallsten R, Owusu Obeng A, Botton MR, Cody N, Shi H, Zhao G, Brake P, Nicoletti P, Yang Y, Delio M, Shi L, Kornreich R, Schadt EE, Edelmann L. Development and Analytical Validation of a 29 Gene Clinical Pharmacogenetic Genotyping Panel: Multi-Ethnic Allele and Copy Number Variant Detection. Clin Transl Sci 2020; 14:204-213. [PMID: 32931151 PMCID: PMC7877843 DOI: 10.1111/cts.12844] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 06/16/2020] [Indexed: 12/12/2022] Open
Abstract
To develop a novel pharmacogenetic genotyping panel, a multidisciplinary team evaluated available evidence and selected 29 genes implicated in interindividual drug response variability, including 130 sequence variants and additional copy number variants (CNVs). Of the 29 genes, 11 had guidelines published by the Clinical Pharmacogenetics Implementation Consortium. Targeted genotyping and CNV interrogation were accomplished by multiplex single‐base extension using the MassARRAY platform (Agena Biosciences) and multiplex ligation‐dependent probe amplification (MRC Holland), respectively. Analytical validation of the panel was accomplished by a strategic combination of > 500 independent tests performed on 170 unique reference material DNA samples, which included sequence variant and CNV accuracy, reproducibility, and specimen (blood, saliva, and buccal swab) controls. Among the accuracy controls were 32 samples from the 1000 Genomes Project that were selected based on their enrichment of sequence variants included in the pharmacogenetic panel (VarCover.org). Coupled with publicly available samples from the Genetic Testing Reference Materials Coordination Program (GeT‐RM), accuracy validation material was available for the majority (77%) of interrogated sequence variants (100% with average allele frequencies > 0.1%), as well as additional structural alleles with unique copy number signatures (e.g., CYP2D6*5, *13, *36, *68; CYP2B6*29; and CYP2C19*36). Accuracy and reproducibility for both genotyping and copy number were > 99.9%, indicating that the optimized panel platforms were precise and robust. Importantly, multi‐ethnic allele frequencies of the interrogated variants indicate that the vast majority of the general population carries at least one of these clinically relevant pharmacogenetic variants, supporting the implementation of this panel for pharmacogenetic research and/or clinical implementation programs.
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Affiliation(s)
- Stuart A Scott
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Erick R Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | | | | | - Aniwaa Owusu Obeng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mariana R Botton
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Neal Cody
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | | | | | - Paola Nicoletti
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Yao Yang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Lisong Shi
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ruth Kornreich
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Eric E Schadt
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Lisa Edelmann
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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85
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Ionova Y, Ashenhurst J, Zhan J, Nhan H, Kosinski C, Tamraz B, Chubb A. CYP2C19 Allele Frequencies in Over 2.2 Million Direct-to-Consumer Genetics Research Participants and the Potential Implication for Prescriptions in a Large Health System. Clin Transl Sci 2020; 13:1298-1306. [PMID: 32506666 PMCID: PMC7719394 DOI: 10.1111/cts.12830] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 05/08/2020] [Indexed: 01/03/2023] Open
Abstract
Understanding the prevalence of clinically relevant pharmacogenetic variants using large unselected populations is critical for gauging the potential clinical impact of widespread preemptive pharmacogenetic testing. To this end, we assessed the frequencies and ethnic distribution of the three most common CYP2C19 alleles (*2, *3, and *17) in 2.29 million direct-to-consumer genetics research participants (23andMe, Sunnyvale, CA). The overall frequencies of *2, *3, and *17 were 15.2%, 0.3%, and 20.4%, respectively, but varied by ethnicity. The most common variant diplotypes were *1/*17 at 26% and *1/*2 at 19.4%. The less common *2/*17, *17/*17, and *2/*2 genotypes occurred at 6.0%, 4.4%, and 2.5%, respectively. Overall, 58.3% of participants had at least one increased-function or no-function CYP2C19 allele. To better understand how this high frequency might impact a real patient population, we examined the prescription rates (Rx) of high-pharmacogenetic-risk medications metabolized by CYP2C19 using the University of California at San Francisco (UCSF) health system's anonymized database of over 1.25 million patients. Between 2012 and 2019, a total of 151,068 UCSF patients (15.8%) representing 5 self-reported ethnicities were prescribed one or more high-pharmacogenetic-risk CYP2C19 medications: proton pump inhibitors (145,243 Rx), three selective serotonin reuptake inhibitor antidepressants (54,463 Rx), clopidogrel (14,376 Rx), and voriconazole (2,303 Rx).
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Affiliation(s)
- Yelena Ionova
- School of Pharmacy, University of California, San Francisco, California, USA
| | | | | | - Hoang Nhan
- 23andMe, Inc., Sunnyvale, California, USA
| | | | - Bani Tamraz
- School of Pharmacy, University of California, San Francisco, California, USA
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86
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Carr DF, Turner RM, Pirmohamed M. Pharmacogenomics of anticancer drugs: Personalising the choice and dose to manage drug response. Br J Clin Pharmacol 2020; 87:237-255. [PMID: 32501544 DOI: 10.1111/bcp.14407] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/11/2020] [Accepted: 05/22/2020] [Indexed: 12/13/2022] Open
Abstract
The field of pharmacogenomics has made great strides in oncology over the last 20 years and indeed a significant number of pre-emptive genetic tests are now routinely undertaken prior to anticancer drug administration. Many of these gene-drug interactions are the fruits of candidate gene and genome-wide association studies, which have largely focused on common genetic variants (allele frequency>1%). Examples where there is clinical utility include genotyping or phenotyping for G6PD to prevent rasburicase-induced RBC haemolysis, and TPMT to prevent thiopurine-induced bone marrow suppression. Other associations such as CYP2D6 status in determining the efficacy of tamoxifen are more controversial because of contradictory evidence from different sources, which has led to variability in the implementation of testing. As genomic technology becomes ever cheaper and more accessible, we must look to the additional data our genome can provide to explain interindividual variability in anticancer drug response. Clearly genes do not act on their own and it is therefore important to investigate genetic factors in conjunction with clinical factors, interacting concomitant drug therapies and other factors such as the microbiome, which can all affect drug disposition. Taking account of all of these factors, in conjunction with the somatic genome, is more likely to provide better predictive accuracy in determining anticancer drug response, both efficacy and safety. This review summarises the existing knowledge related to the pharmacogenomics of anticancer drugs and discusses areas of opportunity for further advances in personalisation of therapy in order to improve both drug safety and efficacy.
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Affiliation(s)
- Daniel F Carr
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Richard M Turner
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Munir Pirmohamed
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
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87
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Black RM, Williams AK, Ratner L, Crona DJ, Wiltshire T, Weck KE, Stouffer GA, Lee CR. Projected impact of pharmacogenomic testing on medications beyond antiplatelet therapy in percutaneous coronary intervention patients. Pharmacogenomics 2020; 21:431-441. [PMID: 32343201 DOI: 10.2217/pgs-2019-0185] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Aim: CYP2C19 genotyping is used to guide antiplatelet therapy after percutaneous coronary intervention (PCI). This study evaluated the potential impact of CYP2C19 and multigene pharmacogenomics (PGx) testing on medications beyond antiplatelet therapy in a real-world cohort of PCI patients that underwent CYP2C19 testing. Methodology & results: Multiple medications with actionable PGx recommendations, including proton pump inhibitors, antidepressants and opioids, were commonly prescribed. Approximately 50% received a CYP2C19 metabolized medication beyond clopidogrel and 7% met criteria for a CYP2C19 genotype-guided intervention. A simulation analysis projected that 17.5 PGx-guided medication interventions per 100 PCI patients could have been made if multigene PGx results were available. Conclusion: This suggests that CYP2C19 and multigene PGx results could be used to optimize medication prescribing beyond antiplatelet therapy in PCI patients.
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Affiliation(s)
- Rachel M Black
- Division of Pharmacotherapy & Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Alexis K Williams
- Division of Pharmacotherapy & Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lindsay Ratner
- Division of Pharmacotherapy & Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Daniel J Crona
- Division of Pharmacotherapy & Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tim Wiltshire
- Division of Pharmacotherapy & Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Karen E Weck
- Department of Pathology & Laboratory Medicine, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - George A Stouffer
- Division of Cardiology, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.,UNC McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Craig R Lee
- Division of Pharmacotherapy & Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.,UNC McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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88
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McDonough CW, Breitenstein MK, Shahin M, Empey PE, Freimuth RR, Li L, Liebman M, Tuteja S. Translational Informatics Connects Real-World Information to Knowledge in an Increasingly Data-Driven World. Clin Pharmacol Ther 2020; 107:738-741. [PMID: 31837229 PMCID: PMC7678684 DOI: 10.1002/cpt.1719] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 11/01/2019] [Indexed: 11/07/2022]
Affiliation(s)
| | | | | | | | | | - Lang Li
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH
| | | | - Sony Tuteja
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
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89
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Abstract
PURPOSE OF REVIEW Update findings regarding polypharmacy among people with HIV (PWH) and consider what research is most needed. RECENT FINDINGS Among PWH, polypharmacy is common, occurs in middle age, and is predominantly driven by nonantiretroviral (ARV) medications. Many studies have demonstrated strong associations between polypharmacy and receipt of potentially inappropriate medications (PIMS), but few have considered actual adverse events. Falls, delirium, pneumonia, hospitalization, and mortality are associated with polypharmacy among PWH and risks remain after adjustment for severity of illness. SUMMARY Polypharmacy is a growing problem and mechanisms of injury likely include potentially inappropriate medications, total drug burden, known pairwise drug interactions, higher level drug interactions, drug--gene interactions, and drug--substance use interactions (alcohol, extra-medical prescription medication, and drug use). Before we can effectively design interventions, we need to use observational data to gain a better understanding of the modifiable mechanisms of injury. As sicker individuals take more medications, analyses must account for severity of illness. As self-report of substance use may be inaccurate, direct biomarkers, such as phosphatidylethanol (PEth) for alcohol are needed. Large samples including electronic health records, genetics, accurate measures of substance use, and state of the art statistical and artificial intelligence techniques are needed to advance our understanding and inform clinical management of polypharmacy in PWH.
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Affiliation(s)
| | - Christopher T. Rentsch
- VA Connecticut Healthcare System, West Haven, CT
- London School of Hygiene & Tropical Medicine, London, UK
| | - Amy C. Justice
- Yale Schools of Medicine and Public Health, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
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90
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El Rouby N, Alrwisan A, Langaee T, Lipori G, Angiolillo DJ, Franchi F, Riva A, Elsey A, Johnson JA, Cavallari LH, Winterstein AG. Clinical Utility of Pharmacogene Panel-Based Testing in Patients Undergoing Percutaneous Coronary Intervention. Clin Transl Sci 2020; 13:473-481. [PMID: 31758664 PMCID: PMC7214641 DOI: 10.1111/cts.12729] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 11/02/2019] [Indexed: 12/19/2022] Open
Abstract
We aimed to estimate the utility of panel‐based pharmacogenetic testing of patients undergoing percutaneous coronary intervention (PCI). Utilization of Clinical Pharmacogenetic Implementation Consortium (CPIC) level A/B drugs after PCI was estimated in a national sample of IBM MarketScan beneficiaries. Genotype data from University of Florida (UF) patients (n = 211) who underwent PCI were used to project genotype‐guided opportunities among MarketScan beneficiaries with at least one (N = 105,547) and five (N = 12,462) years of follow‐up data. The actual incidence of genotype‐guided prescribing opportunities was determined among UF patients. In MarketScan, 50.0% (52,799/105,547) over 1 year and 68.0% (8,473/12,462) over 5 years had ≥ 1 CPIC A/B drug besides antiplatelet therapy prescribed, with a projected incidence of genotype‐guided prescribing opportunities of 39% at 1 year and 52% at 5 years. Genotype‐guided prescribing opportunities occurred in 32% of UF patients. Projected and actual incidence of genotype‐guided opportunities among two cohorts supports the utility of panel‐based testing among patients who underwent PCI.
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Affiliation(s)
- Nihal El Rouby
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA.,Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Adel Alrwisan
- Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, Florida, USA.,Saudi Food and Drug Authority, Riyadh, Saudi Arabia
| | - Taimour Langaee
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA.,Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Gloria Lipori
- Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, Florida, USA.,UF Health & UF Health Sciences Center, Gainesville, Florida, USA
| | - Dominick J Angiolillo
- Division of Cardiology, Department of Medicine, University of Florida, Jacksonville, Florida, USA
| | - Francesco Franchi
- Division of Cardiology, Department of Medicine, University of Florida, Jacksonville, Florida, USA
| | - Alberto Riva
- Bioinformatics Core, Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, Florida, USA
| | - Amanda Elsey
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA.,Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA.,Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Almut G Winterstein
- Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, Florida, USA.,Epidemiology, University of Florida, Gainesville, Florida, USA.,Center for Drug Evaluation and Safety, University of Florida, Gainesville, Florida, USA
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