Evidence map›Paper›PMID 33999485›Full record

ArticleAddiction (Abingdon, England)2021

Impact of treatment duration on mortality among Veterans with opioid use disorder in the United States Veterans Health Administration.

Jack H Ching, Douglas K Owens, Jodie A Trafton, Jeremy D Goldhaber-Fiebert, Joshua A Salomon

Open access · greenAbstract read
In one paragraph

Article in Addiction (Abingdon, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 12 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

5 authors at 2 institutions in 1 country.

Jack H ChingCenter for Health Policy and Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0003-0752-8628
Douglas K OwensCenter for Health Policy and Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, CA, USA.
Jodie A TraftonProgram Evaluation and Resource Center, Office of Mental Health and Suicide Prevention, VA Palo Alto Health Care System, Menlo Park, CA, USA.
Jeremy D Goldhaber-FiebertCenter for Health Policy and Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, CA, USA.
Joshua A SalomonCenter for Health Policy and Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0003-3929-5515
VA Palo Alto Health Care System · USStanford Health Care · US

Funding

Making Better Decisions: Policy Modeling for AIDS and Drug AbuseR37DA015612 · NIDA · STANFORD UNIVERSITY · PI DOUGLAS K OWENS · 2019 to 2026
$6.3M
Stanford Health Services Research Training ProgramT32HS026128 · AHRQ · STANFORD UNIVERSITY · PI BAKER, LAURENCE C, OWENS, DOUGLAS K · 2018 to 2024
$3.6M
Improving Opioid Use Disorder Treatment within the Veterans Health AdministrationR36HS027935 · AHRQ · STANFORD UNIVERSITY · PI CHING, JACK HORN-YU · 2020 to 2020
$40k
AHRQ HHS R36 HS027935AHRQ HHS T32 HS026128NIDA NIH HHS R37 DA015612
6 · The paper itself

Abstract

BACKGROUND AND

aimsWhile long-term medication-assisted treatment (MAT) using methadone or buprenorphine is associated with significantly lower all-cause mortality for individuals with opioid use disorder (OUD), periods of initiating or discontinuing treatment are associated with higher mortality risks relative to stable treatment. This study aimed to identify the OUD treatment durations necessary for the elevated mortality risks during treatment transitions to be balanced by reductions in mortality while receiving treatment.

designSimulation model based on a compartmental model of OUD diagnosis, MAT receipt and all-cause mortality among Veterans with OUD in the United States Veterans Health Administration (VA) in 2017-2018. We simulated methadone and buprenorphine treatments of varying durations using parameters obtained through calibration and published meta-analyses of studies from North America, Europe and Australia.

settingUnited States.

participantsSimulated cohorts of 10 000 individuals with OUD. MEASUREMENTS: All-cause mortality over 12 months.

findingsReceiving methadone for 4 months or longer or buprenorphine for 2 months or longer resulted in 54 [95% confidence interval (CI) = 5-90] and 65 (95% CI = 21-89) fewer deaths relative to not receiving MAT for the same duration, using VA-specific mortality rates. We estimated shorter treatment durations necessary to achieve net mortality benefits of 2 months or longer for methadone and 1 month or longer for buprenorphine, using non-VA population literature estimates. Sensitivity analyses demonstrated that necessary treatment durations increased more with smaller mortality reductions on treatment than with larger relative risks during treatment transitions.

conclusionsShort periods (< 6 months) of treatment with either methadone or buprenorphine are likely to yield net mortality benefits for people with opioid use disorder relative to receiving no medications, despite periods of elevated all-cause mortality risk during transitions into and out of treatment. Retaining people with opioid use disorder in treatment longer can increase these benefits.

Indexed as

BuprenorphineOpioid-Related DisordersVeteransAnalgesics, OpioidDuration of TherapyHumansMethadoneOpiate Substitution TreatmentUnited StatesVeterans HealthAnalgesics, OpioidBuprenorphineMethadoneBuprenorphinemedications for addiction treatmentmethadoneopioid use disordersimulation modelingVeterans

Identifiers

PMID33999485
PMCPMC8578188
OpenAlexW3162942920

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.