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. 2014 Jul 1:140:69-77.
doi: 10.1016/j.drugalcdep.2014.03.029. Epub 2014 Apr 8.

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

B Nosyk  1 , L Li  2 , E Evans  2 , D Huang  2 , J Min  3 , T Kerr  4 , M L Brecht  2 , Y I Hser  5
Affiliations

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

B Nosyk et al. Drug Alcohol Depend. .

Abstract

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

Design: Pooled analysis of prospective cohort studies.

Settings: Illicit drug users recruited from community, criminal justice and drug treatment settings in California, USA.

Participants: We 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.

Findings: Across 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.

Conclusions: PH 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.

Keywords: Drug use careers; Health state transitions; Longitudinal; Multi-state Markov; Proportional hazards frailty.

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Figures

Figure 1
Figure 1
Estimated health state transition probabilities, by primary drug of abuse
Figure 1
Figure 1
Estimated health state transition probabilities, by primary drug of abuse
Figure 1
Figure 1
Estimated health state transition probabilities, by primary drug of abuse
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References

    1. Amato L, Davoli M, Perucci CA, Ferri M, Faggiano F, Mattick RP. An overview of systematic reviews of the effectiveness of opiate maintenance therapies: available evidence to inform clinical practice and research. J. Subst. Abuse Treat. 2005;28:321–329. - PubMed
    1. Anglin MD, Hser YI, Chou C. Reliability and validity of retrospective behavioral self-report by narcotics addicts. Eval. Rev. 1993;17:91–108.
    1. Balster RL, Singleton J, Degenhardt L, Hall W, Zabransky T. Mortality among amphetamine users: a systematic review of cohort studies. Drug Alcohol Depend. 2009;105:1–8. - PubMed
    1. Bart G. Maintenance medication for opiate addiction: the foundation of recovery. J. Addict. Dis. 2012;31:207–225. - PMC - PubMed
    1. Bell J, Burrell T, Indig D, Gilmour S. Cycling in and out of treatment; participation in methadone treatment in NSW, 1990-2002. Drug Alcohol Depend. 2006;81:55–61. - PubMed

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