Opioid Drug-Drug-Drug Interactions and Unintentional Traumatic Injury: Screening to Detect Three-Way Drug Interaction Signals.

drug interactions injury opioid analgesics pharmacoepidemiology population health self-controlled case series

Journal

Frontiers in pharmacology
ISSN: 1663-9812
Titre abrégé: Front Pharmacol
Pays: Switzerland
ID NLM: 101548923

Informations de publication

Date de publication:
2022
Historique:
received: 29 12 2021
accepted: 18 04 2022
entrez: 27 5 2022
pubmed: 28 5 2022
medline: 28 5 2022
Statut: epublish

Résumé

Growing evidence suggests that drug interactions may be responsible for much of the known association between opioid use and unintentional traumatic injury. While prior research has focused on pairwise drug interactions, the role of higher-order (i.e., drug-drug-drug) interactions (3DIs) has not been examined. We aimed to identify signals of opioid 3DIs with commonly co-dispensed medications leading to unintentional traumatic injury, using semi-automated high-throughput screening of US commercial health insurance data. We conducted bi-directional, self-controlled case series studies using 2000-2015 Optum Data Mart database. Rates of unintentional traumatic injury were examined in individuals dispensed opioid-precipitant base pairs during time exposed vs unexposed to a candidate interacting precipitant. Underlying cohorts consisted of 16-90-year-olds with new use of opioid-precipitant base pairs and ≥1 injury during observation periods. We used conditional Poisson regression to estimate rate ratios adjusted for time-varying confounders, and semi-Bayes shrinkage to address multiple estimation. For hydrocodone, tramadol, and oxycodone (the most commonly used opioids), we examined 16,024, 8185, and 9330 drug triplets, respectively. Among these, 75 (0.5%; hydrocodone), 57 (0.7%; tramadol), and 42 (0.5%; oxycodone) were significantly positively associated with unintentional traumatic injury (50 unique base precipitants, 34 unique candidate precipitants) and therefore deemed potential 3DI signals. The signals found in this study provide valuable foundations for future research into opioid 3DIs, generating hypotheses to motivate crucially needed etiologic investigations. Further, this study applies a novel approach for 3DI signal detection using pharmacoepidemiologic screening of health insurance data, which could have broad applicability across drug classes and databases.

Identifiants

pubmed: 35620282
doi: 10.3389/fphar.2022.845485
pii: 845485
pmc: PMC9127150
doi:

Types de publication

Journal Article

Langues

eng

Pagination

845485

Informations de copyright

Copyright © 2022 Acton, Hennessy, Brensinger, Bilker, Miano, Dublin, Horn, Chung, Wiebe, Willis and Leonard.

Déclaration de conflit d'intérêts

SC was employed by the company AthenaHealth, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Emily K Acton (EK)

Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.

Sean Hennessy (S)

Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States.
Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.

Colleen M Brensinger (CM)

Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.

Warren B Bilker (WB)

Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
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.

Todd A Miano (TA)

Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.

Sascha Dublin (S)

Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, United States.
Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States.

John R Horn (JR)

Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, United States.

Sophie Chung (S)

AthenaHealth, Inc., Watertown, MA, United States.

Douglas J Wiebe (DJ)

Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States.
Penn Injury Science Center, University of Pennsylvania, Philadelphia, PA, United States.

Allison W Willis (AW)

Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States.

Charles E Leonard (CE)

Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States.

Classifications MeSH