Evidence map›Paper›PMID 37794260›Full record

ArticleJournal of general internal medicine2024

Impact of 30-day prescribed opioid dose trajectory on fatal overdose risk: A population-based, statewide cohort study.

Stephen G Henry, Shao-You Fang, Andrew J Crawford, Garen J Wintemute, Iraklis Erik Tseregounis, James J Gasper, Aaron Shev, Abigail R Cartus, Brandon D L Marshall, Daniel J Tancredi and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of general internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. De-prescribing opioids among Medicaid patients with long-term opioid use.Journal of substance use and addiction treatment · 2025
    Article
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

12 authors at 6 institutions in 1 country.

Stephen G HenryUniversity of California Davis Center for Healthcare Policy and Research; University of California, Davis, California, Sacramento, USA. sghenry@ucdavis.edu.ORCID 0000-0002-5643-0881
Shao-You FangUniversity of California Davis Center for Healthcare Policy and Research; University of California, Davis, California, Sacramento, USA.
Andrew J CrawfordViolence Prevention Research Program; University of California, Davis, California, Sacramento, USA.
Garen J WintemuteViolence Prevention Research Program; University of California, Davis, California, Sacramento, USA.
Iraklis Erik TseregounisUniversity of California Davis Center for Healthcare Policy and Research; University of California, Davis, California, Sacramento, USA.
James J GasperDepartment of Family and Community Medicine, University of California, San Francisco, California, San Francisco, USA.
Aaron ShevViolence Prevention Research Program; University of California, Davis, California, Sacramento, USA.
Abigail R CartusDepartment of Epidemiology, Brown University School of Public Health, Rhode Island, Providence, USA.
Brandon D L MarshallDepartment of Epidemiology, Brown University School of Public Health, Rhode Island, Providence, USA.
Daniel J TancrediUniversity of California Davis Center for Healthcare Policy and Research; University of California, Davis, California, Sacramento, USA.
Magdalena CerdáDepartment of Population Health, Center for Opioid Epidemiology and Policy; New York University Grossman School of Medicine, New York City, New York, USA.
Susan L StewartDepartment of Public Health Sciences, University of California, Davis, California, Davis, USA.
University of California, Davis · USBrown University · USCenter For Policy Research · USNew York University · USUniversity of California, San Francisco · USUniversity of California System · US

Funding

Developing Patient-level Risk Prediction Models for Prescription Opioid OverdoseR01DA044282 · NIDA · UNIVERSITY OF CALIFORNIA AT DAVIS · PI HENRY, STEPHEN G · 2017 to 2020
$2.5M
NIDA NIH HHS R01 DA044282NIDA NIH HHS R01DA044282
6 · The paper itself

Abstract

backgroundBoth increases and decreases in patients' prescribed daily opioid dose have been linked to increased overdose risk, but associations between 30-day dose trajectories and subsequent overdose risk have not been systematically examined.

objectiveTo examine the associations between 30-day prescribed opioid dose trajectories and fatal opioid overdose risk during the subsequent 15 days.

designStatewide cohort study using linked prescription drug monitoring program and death certificate data. We constructed a multivariable Cox proportional hazards model that accounted for time-varying prescription-, prescriber-, and pharmacy-level factors.

participantsAll patients prescribed an opioid analgesic in California from March to December, 2013 (5,326,392 patients). MAIN MEASURES: Dependent variable: fatal drug overdose involving opioids. Primary independent variable: a 16-level variable denoting all possible opioid dose trajectories using the following categories for current and 30-day previously prescribed daily dose: 0-29, 30-59, 60-89, or ≥90 milligram morphine equivalents (MME). KEY

resultsRelative to patients prescribed a stable daily dose of 0-29 MME, large (≥2 categories) dose increases and having a previous or current dose ≥60 MME per day were associated with significantly greater 15-day overdose risk. Patients whose dose decreased from ≥90 to 0-29 MME per day had significantly greater overdose risk compared to both patients prescribed a stable daily dose of ≥90 MME (aHR 3.56, 95%CI 2.24-5.67) and to patients prescribed a stable daily dose of 0-29 MME (aHR 7.87, 95%CI 5.49-11.28). Patients prescribed benzodiazepines also had significantly greater overdose risk; being prescribed Z-drugs, carisoprodol, or psychostimulants was not associated with overdose risk.

conclusionsLarge (≥2 categories) 30-day dose increases and decreases were both associated with increased risk of fatal opioid overdose, particularly for patients taking ≥90 MME whose opioids were abruptly stopped. Results align with 2022 CDC guidelines that urge caution when reducing opioid doses for patients taking long-term opioid for chronic pain.

Indexed as

Drug OverdoseOpiate OverdoseAnalgesics, OpioidCohort StudiesEndrinHumansPractice Patterns, Physicians'Retrospective StudiesAnalgesics, OpioidEndrinMMEcontrolled substancesdrug overdosedrug taperingopiate overdoseopioid analgesicsprescription drug monitoring programsrisk factors

Identifiers

PMID37794260
PMCPMC10897080
OpenAlexW4387345034

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.