Evidence map›Paper›PMID 35620282›Full record

ArticleFrontiers in pharmacology2022

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

Emily K Acton, Sean Hennessy, Colleen M Brensinger, Warren B Bilker, Todd A Miano, Sascha Dublin, John R Horn, Sophie Chung, Douglas J Wiebe, Allison W Willis and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 6 institutions in 1 country.

Emily K ActonCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Sean HennessyCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Colleen M BrensingerCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Warren B BilkerCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Todd A MianoCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Sascha DublinKaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, United States.
John R HornDepartment of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, United States.
Sophie ChungAthenaHealth, Inc., Watertown, MA, United States.
Douglas J WiebeDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Allison W WillisCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Charles E LeonardCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
University of Pennsylvania · USathenahealth · USKaiser Permanente Washington Health Research Institute · USPenn Center for AIDS Research · USTranslational Therapeutics (United States) · USUniversity of Washington · US

Funding

Clinical Importance of Drug-Drug InteractionsR01AG025152 · NIA · UNIVERSITY OF PENNSYLVANIA · PI HENNESSY, SEAN, LI, LANG · 2006 to 2021
$8.1M
Drug interactions involving psychoactive drugsR01AG060975 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Charles Edward Leonard · 2019 to 2026
$3.9M
Drug-Drug Interactions Involving Methadone and BuprenorphineR01DA048001 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI HENNESSY, SEAN · 2019 to 2023
$2.9M
NIA NIH HHS R01 AG025152NIA NIH HHS R01 AG060975NIDA NIH HHS R01 DA048001
6 · The paper itself

Abstract

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.

Indexed as

drug interactionsinjuryopioid analgesicspharmacoepidemiologypopulation healthself-controlled case series

Identifiers

PMID35620282
PMCPMC9127150
OpenAlexW4229443890

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.