Evidence map›Paper›PMID 24837584›Full record

ArticleDrug and alcohol dependence2014

Characterizing longitudinal health state transitions among heroin, cocaine, and methamphetamine users.

B Nosyk, L Li, E Evans, D Huang, J Min, T Kerr, M L Brecht, Y I Hser

Abstract read
In one paragraph

Article in Drug and alcohol dependence, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  18. Estimating State Transitions for Opioid Use Disorders.Medical decision making : an international journal of the Society for Medical Decision Making · 2017
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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

8 authors.

B NosykBC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia V6Z 2C7, Canada; Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada; UCLA Integrated Substance Abuse Programs, Los Angeles, CA 90025, USA.
L LiUCLA Integrated Substance Abuse Programs, Los Angeles, CA 90025, USA.
E EvansUCLA Integrated Substance Abuse Programs, Los Angeles, CA 90025, USA.
D HuangUCLA Integrated Substance Abuse Programs, Los Angeles, CA 90025, USA.
J MinBC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia V6Z 2C7, Canada.
T KerrBC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia V6Z 2C7, Canada; Division of AIDS, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia V5Z 1M9, Canada.
M L BrechtUCLA Integrated Substance Abuse Programs, Los Angeles, CA 90025, USA.
Y I HserUCLA Integrated Substance Abuse Programs, Los Angeles, CA 90025, USA. Electronic address: yhser@ucla.edu.

Funding

STATISTICAL SUPPORT/DATA MANAGEMENT COREP30DA016383 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HSER, YIH-ING · 2005 to 2015
$8.6M
Seek and Treat for Optimal Prevention of HIV & AIDS (STOP HIV/AIDS) in BCR01DA036307 · NIDA · UNIVERSITY OF BRITISH COLUMBIA · PI MONTANER, JULIO SERGIO GONZALEZ · 2013 to 2017
$3.0M
A Comparison of Methadone Treatment Systems in California and British ColumbiaR01DA031727 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI NOSYK, BOHDAN · 2011 to 2013
$512k
An empirical investigation into recovery from illicit drug abuse using recurrentR01DA032551 · NIDA · UNIVERSITY OF BRITISH COLUMBIA · PI MONTANER, JULIO SERGIO GONZALEZ, NOSYK, BOHDAN · 2012 to 2014
$500k
NIDA NIH HHS P30 DA016383NIDA NIH HHS P30DA016383NIDA NIH HHS R01 DA031727NIDA NIH HHS R01DA031727-01NIDA NIH HHS R01 DA032551NIDA NIH HHS R01DA032551NIDA NIH HHS R01 DA036307
6 · The paper itself

Abstract

aimsCharacterize longitudinal patterns of drug use careers and identify determinants of drug use frequency across cohorts of primary heroin, methamphetamine (MA) and cocaine users.

designPooled analysis of prospective cohort studies. SETTINGS: Illicit drug users recruited from community, criminal justice and drug treatment settings in California, USA.

participantsWe used longitudinal data on from five observational cohort studies featuring primary users of heroin (N=629), cocaine (N=694) and methamphetamine (N=474). The mean duration of follow-up was 20.9 years. MEASUREMENTS: Monthly longitudinal data was arranged according to five health states (incarceration, drug treatment, abstinence, non-daily and daily use). We fitted proportional hazards (PH) frailty models to determine independent differences in successive episode durations. We then executed multi-state Markov (MSM) models to estimate probabilities of transitioning between health states, and the determinants of these transitions.

findingsAcross primary drug use types, PH frailty models demonstrated durations of daily use diminished in successive episodes over time. MSM models revealed primary stimulant users had more erratic longitudinal patterns of drug use, transitioning more rapidly between periods of treatment, abstinence, non-daily and daily use. MA users exhibited relatively longer durations of high-frequency use. Criminal engagement had a destabilizing effect on health state durations across drug types. Longer incarceration histories were associated with delayed transitions toward cessation.

conclusionsPH frailty and MSM modeling techniques provided complementary information on longitudinal patterns of drug abuse. This information can inform clinical practice and policy, and otherwise be used in health economic simulation models, designed to inform resource allocation decisions.

Indexed as

AdultAmphetamine-Related DisordersCaliforniaCentral Nervous System StimulantsCocaine-Related DisordersCohort StudiesCrimeFemaleFollow-Up StudiesHealth StatusHeroin DependenceHumansLongitudinal StudiesMaleMethamphetamineMiddle AgedCentral Nervous System StimulantsMethamphetamineDrug use careersHealth state transitionsLongitudinalMulti-state MarkovProportional hazards frailty

Identifiers

PMID24837584
PMCPMC4072125

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.