Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury
Background: Efforts to minimize harms from opioid drug interactions may be hampered by limited evidence on which drugs, when taken concomitantly with opioids, result in adverse clinical outcomes. Objective: To identify signals of opioid drug interactions by identifying concomitant medications (preci...
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Elsevier
2020-10-01
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Series: | Biomedicine & Pharmacotherapy |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S0753332220307241 |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Charles E. Leonard Colleen M. Brensinger Thanh Phuong Pham Nguyen John R. Horn Sophie Chung Warren B. Bilker Sascha Dublin Samantha E. Soprano Ghadeer K. Dawwas David W. Oslin Douglas J. Wiebe Sean Hennessy |
spellingShingle |
Charles E. Leonard Colleen M. Brensinger Thanh Phuong Pham Nguyen John R. Horn Sophie Chung Warren B. Bilker Sascha Dublin Samantha E. Soprano Ghadeer K. Dawwas David W. Oslin Douglas J. Wiebe Sean Hennessy Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury Biomedicine & Pharmacotherapy Drug interactions Injury Opioid analgesics Pharmacoepidemiology Population health Self-controlled case series |
author_facet |
Charles E. Leonard Colleen M. Brensinger Thanh Phuong Pham Nguyen John R. Horn Sophie Chung Warren B. Bilker Sascha Dublin Samantha E. Soprano Ghadeer K. Dawwas David W. Oslin Douglas J. Wiebe Sean Hennessy |
author_sort |
Charles E. Leonard |
title |
Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury |
title_short |
Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury |
title_full |
Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury |
title_fullStr |
Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury |
title_full_unstemmed |
Screening to identify signals of opioid drug interactions leading to unintentional traumatic injury |
title_sort |
screening to identify signals of opioid drug interactions leading to unintentional traumatic injury |
publisher |
Elsevier |
series |
Biomedicine & Pharmacotherapy |
issn |
0753-3322 |
publishDate |
2020-10-01 |
description |
Background: Efforts to minimize harms from opioid drug interactions may be hampered by limited evidence on which drugs, when taken concomitantly with opioids, result in adverse clinical outcomes. Objective: To identify signals of opioid drug interactions by identifying concomitant medications (precipitant drugs) taken with individual opioids (object drugs) that are associated with unintentional traumatic injury Design: We conducted pharmacoepidemiologic screening of Optum Clinformatics Data Mart, identifying drug interaction signals by performing confounder-adjusted self-controlled case series studies for opioid + precipitant pairs and injury. Setting: Beneficiaries of a major United States-based commercial health insurer during 2000–2015 Patients: Persons aged 16–90 years co-dispensed an opioid and ≥1 precipitant drug(s), with an unintentional traumatic injury event during opioid therapy, as dictated by the case-only design Exposure: Precipitant-exposed (vs. precipitant-unexposed) person-days during opioid therapy. Outcome: Emergency department or inpatient International Classification of Diseases discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to generate confounder adjusted rate ratios. We accounted for multiple estimation via semi-Bayes shrinkage. Results: We identified 25,019, 12,650, and 10,826 new users of hydrocodone, tramadol, and oxycodone who experienced an unintentional traumatic injury. Among 464, 376, and 389 hydrocodone-, tramadol-, and oxycodone-precipitant pairs examined, 20, 17, and 16 (i.e., 53 pairs, 34 unique precipitants) were positively associated with unintentional traumatic injury and deemed potential drug interaction signals. Adjusted rate ratios ranged from 1.23 (95 % confidence interval: 1.05–1.44) for hydrocodone + amoxicillin-clavulanate to 4.21 (1.88–9.42) for oxycodone + telmisartan. Twenty (37.7 %) of 53 signals are currently reported in a major drug interaction knowledgebase. Limitations: Potential for reverse causation, confounding by indication, and chance Conclusions: We identified previously undescribed and/or unappreciated signals of opioid drug interactions associated with unintentional traumatic injury. Subsequent etiologic studies should confirm (or refute) and elucidate these potential drug interactions. |
topic |
Drug interactions Injury Opioid analgesics Pharmacoepidemiology Population health Self-controlled case series |
url |
http://www.sciencedirect.com/science/article/pii/S0753332220307241 |
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doaj-fd6a7a9c408e4979b787885473c933fd2021-05-20T07:43:12ZengElsevierBiomedicine & Pharmacotherapy0753-33222020-10-01130110531Screening to identify signals of opioid drug interactions leading to unintentional traumatic injuryCharles E. Leonard0Colleen M. Brensinger1Thanh Phuong Pham Nguyen2John R. Horn3Sophie Chung4Warren B. Bilker5Sascha Dublin6Samantha E. Soprano7Ghadeer K. Dawwas8David W. Oslin9Douglas J. Wiebe10Sean Hennessy11Center for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Center for Therapeutic Effectiveness Research, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Corresponding author at: Perelman School of Medicine, University of Pennsylvania, 807 Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, United States.Center for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesCenter for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesDepartment of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, United StatesAthenaHealth, Inc., Watertown, MA, United StatesCenter for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesKaiser Permanente Washington Health Research Institute, Seattle, WA, United States; Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United StatesCenter for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesCenter for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesCenter for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Mental Illness Research, Education, and Clinical Center, Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, PA, United StatesDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Injury Science Center, University of Pennsylvania, Philadelphia, PA, United StatesCenter for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Center for Therapeutic Effectiveness Research, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesBackground: Efforts to minimize harms from opioid drug interactions may be hampered by limited evidence on which drugs, when taken concomitantly with opioids, result in adverse clinical outcomes. Objective: To identify signals of opioid drug interactions by identifying concomitant medications (precipitant drugs) taken with individual opioids (object drugs) that are associated with unintentional traumatic injury Design: We conducted pharmacoepidemiologic screening of Optum Clinformatics Data Mart, identifying drug interaction signals by performing confounder-adjusted self-controlled case series studies for opioid + precipitant pairs and injury. Setting: Beneficiaries of a major United States-based commercial health insurer during 2000–2015 Patients: Persons aged 16–90 years co-dispensed an opioid and ≥1 precipitant drug(s), with an unintentional traumatic injury event during opioid therapy, as dictated by the case-only design Exposure: Precipitant-exposed (vs. precipitant-unexposed) person-days during opioid therapy. Outcome: Emergency department or inpatient International Classification of Diseases discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to generate confounder adjusted rate ratios. We accounted for multiple estimation via semi-Bayes shrinkage. Results: We identified 25,019, 12,650, and 10,826 new users of hydrocodone, tramadol, and oxycodone who experienced an unintentional traumatic injury. Among 464, 376, and 389 hydrocodone-, tramadol-, and oxycodone-precipitant pairs examined, 20, 17, and 16 (i.e., 53 pairs, 34 unique precipitants) were positively associated with unintentional traumatic injury and deemed potential drug interaction signals. Adjusted rate ratios ranged from 1.23 (95 % confidence interval: 1.05–1.44) for hydrocodone + amoxicillin-clavulanate to 4.21 (1.88–9.42) for oxycodone + telmisartan. Twenty (37.7 %) of 53 signals are currently reported in a major drug interaction knowledgebase. Limitations: Potential for reverse causation, confounding by indication, and chance Conclusions: We identified previously undescribed and/or unappreciated signals of opioid drug interactions associated with unintentional traumatic injury. Subsequent etiologic studies should confirm (or refute) and elucidate these potential drug interactions.http://www.sciencedirect.com/science/article/pii/S0753332220307241Drug interactionsInjuryOpioid analgesicsPharmacoepidemiologyPopulation healthSelf-controlled case series |