Evidence map›Paper›PMID 35588609›Full record

ArticleDrug and alcohol dependence2022

Modeling of overdose and naloxone distribution in the setting of fentanyl compared to heroin.

Phillip O Coffin, Sigal Maya, James G Kahn

Open access · greenAbstract read
In one paragraph

Article in Drug and alcohol dependence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
6.4field-weighted citation impact, top 3% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  9. Price Sensitivity and Information Barriers to the Take-Up of Naloxone.American economic journal. Economic policy · 2024
    Article
  10. Comparison of theThe Journal of pharmacology and experimental therapeutics · 2024
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  13. Ventilatory Effects of Fentanyl, Heroin, andThe Journal of pharmacology and experimental therapeutics · 2024
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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

3 authors at 1 institution in 1 country.

Phillip O CoffinSan Francisco Department of Public Health, 25 Van Ness Ave Suite 500, San Francisco, CA 94102, United States; University of California San Francisco, 1825 4th St, San Francisco, CA 94158, United States. Electronic address: pcoffin@gmail.com.
Sigal MayaUniversity of California San Francisco, 1825 4th St, San Francisco, CA 94158, United States.
James G KahnUniversity of California San Francisco, 1825 4th St, San Francisco, CA 94158, United States.
University of California, San Francisco · US

Funding

Making Better Decisions: Policy Modeling for AIDS and Drug AbuseR37DA015612 · NIDA · STANFORD UNIVERSITY · PI DOUGLAS K OWENS · 2019 to 2026
$6.3M
Repeated-dose behavioral intervention to reduce opioid overdose: a two-site randomized-controlled efficacy trialR01DA045690 · NIDA · PUBLIC HEALTH FOUNDATION ENTERPRISES · PI COFFIN, PHILLIP O · 2018 to 2022
$4.0M
NIDA NIH HHS R01 DA045690NIDA NIH HHS R37 DA015612
6 · The paper itself

Abstract

backgroundFentanyl has replaced most other non-prescribed opioids in much of North America. There is controversy over whether a hypothetical reduced efficacy of naloxone in reversing fentanyl is a major contributor to the coincident rising overdose mortality.

methodsWe modified an existing Markov decision analytic model of heroin overdose and naloxone distribution to account for known risks of fentanyl by adjusting overdose risk, the likelihood of death in the event of overdose, and the proportion of cases in which available naloxone was administered in time to prevent death. We assumed near-universal survival when naloxone was administered promptly for heroin or fentanyl overdose, but allowed that to decline in sensitivity analyses for fentanyl. We varied the proportion of use that was fentanyl and adjusted the modified parameters accordingly to estimate mortality as the dominant opioid shifted.

resultsAbsent naloxone, the annual overdose death rate was 1.0% and 4.1% for heroin and fentanyl, respectively. With naloxone reaching 80% of those at risk, the overdose death rate was 0.7% and 3.6% for heroin and fentanyl, respectively, representing reductions of 26.4% and 12.0%. Monte Carlo simulations resulted in overdose mortality with fentanyl of 3.3-5.2% without naloxone and 2.6-4.9% with naloxone, with 95% certainty. Positing reduced efficacy for naloxone in reversing fentanyl resulted in 3.6% of fentanyl overdose deaths being prevented by naloxone.

conclusionsHeightened risk for overdose and subsequent death, alongside the time-sensitive need for naloxone administration, fully account for increased mortality when fentanyl replaces heroin, assuming optimal pharmacologic efficacy of naloxone.

Indexed as

Drug OverdoseOpiate OverdoseAnalgesics, OpioidFentanylHeroinHumansNaloxoneNarcotic AntagonistsAnalgesics, OpioidFentanylHeroinNaloxoneNarcotic AntagonistsFentanylHeroinModelingNaloxoneOverdose

Identifiers

PMID35588609
PMCPMC9235402
OpenAlexW4225293048

What OpenQuestion holds

Textmetadata
LicenceTDM
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.