Predicting Cocaine Use Among Methadone Patients: Analysis of Findings From a National Study

Research Triangle Institute, Research Triangle Park, NC 27709.
Hospital & community psychiatry 07/1992; 43(6):608-11. DOI: 10.1176/ps.43.6.608
Source: PubMed

ABSTRACT Findings from a large-scale national study of clients admitted to publicly funded drug treatment programs between 1979 and 1981 were used to determine whether cocaine use by current and former methadone patients could be predicted. The sample for this analysis comprised 526 daily or weekly heroin users admitted to 17 methadone maintenance programs. The study found that cocaine use by both current and former methadone patients showed an overall decline during the follow-up year; that patients who stopped using heroin after entering treatment were much more likely to quit using cocaine than were their heroin-using counterparts; and that the odds of initiating cocaine use after admission to a methadone program were much higher among patients who continued using heroin. These findings suggest that methadone programs may be able to reduce cocaine use among some patients by improving their effectiveness in reducing heroin use.

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    • "Thus, they have a worse prognosis with respect to cocaine use than those who manage to abstain from heroin (Dunteman et al., 1992; DeMaria et al., 2000). Dunteman et al. (1992) showed that patients who used cocaine during preadmission to MMT and continued using heroin while in treatment were three and a half times more likely to continue using cocaine than patients who stopped using heroin during this period; moreover, patients who did not use cocaine before admission were three times more likely to start using cocaine if they continued to use heroin during one follow-up year. Secondly, it is possible that the sample size in some of our subanalyses may have limited our ability to detect potentially important associa- tions. "
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    ABSTRACT: To evaluate the effect of methadone maintenance treatment (MMT) on cocaine use and cocaine injection among heroin users. Generalized estimating equations (GEE) were used to examine the association between MMT enrollment (0, <12, ≥12 months) and changes in frequency of cocaine use or injection in two consecutive follow-up visits among heroin users in the Itinere cohort, and to determine whether these changes were independent of equivalent changes in heroin use or injection. Seven multivariate models were constructed, one for each outcome variable on drug use changes. Of the 992 participants recruited in 2001-2003, 628 (63.3%) had at least one follow-up visit. Of these, 55.8% were enrolled in MMT at baseline and an additional 23.2% initiated MMT during follow-up. In multivariate GEE, changes significantly and positively associated with MMT enrollment were: less cocaine use [MMT<12 months (OR=1.70, 95% CI=1.17-2.48)] and less cocaine injection [MMT≥12 months (OR=2.98, 95% CI=1.51-5.89)]. Being on MMT≥12 months was negatively associated with more cocaine use (OR=0.62, 95% CI=0.38-0.99) and with more cocaine injection (OR=0.52, 95% CI=0.28-0.98). When equivalent changes in heroin were used as a covariate, the MMT effect on less cocaine use was hardly modified (OR=1.69, 95% CI=1.07-2.65), and the effect on changes in cocaine injection disappeared. MMT enrollment is a protective factor against both cocaine use and injection among heroin users. The effect of MMT on cocaine injection appears to be mediated by heroin injection, whereas its effect on cocaine use is more direct.
    Drug and alcohol dependence 11/2010; 112(1-2):62-8. DOI:10.1016/j.drugalcdep.2010.05.014 · 3.28 Impact Factor
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    • "It is unclear is how these findings in rats speak to effectiveness of SSM maintenance in reducing cocaine addiction in humans, as clinical studies on this subject have yielded inconsistent findings (Bux et al. 1995; Dunteman et al. 1992; Foltin et al. 1995; Foltin and Fischman 1996; Kosten et al. 1986; Maremmani et al. 2007; Peles et al. 2006). Also unclear is how SSM prevented the expression of neural adaptations associated with cocaine exposure and cocaine conditioning. "
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    ABSTRACT: To elucidate the effects of steady-state methadone exposure on responding to cocaine conditioned stimuli and on cocaine-induced alterations in central opioid, hypocretin/orexin, and D2 receptor systems, male Sprague-Dawley rats received intravenous infusions of 1 mg/kg/inf cocaine paired with an audiovisual stimulus over three days of conditioning. Then, mini pumps releasing vehicle or 30 mg/kg/day methadone were implanted (SC), and lever pressing for the stimulus was assessed in the absence of cocaine and after a cocaine prime (20 mg/kg, IP). It was found that rats treated with vehicle, but not methadone, responded for the cocaine conditioned stimulus and displayed elevated mu-opioid receptor mRNA expression in the nucleus accumbens core and basolateral amygdala, reduced hypocretin/orexin mRNA in the lateral hypothalamus, and reduced D2 receptor mRNA in the caudate-putamen. This is the first demonstration that steady-state methadone administered after cocaine exposure blocks cocaine-induced behavioral and neural adaptations.
    European neuropsychopharmacology: the journal of the European College of Neuropsychopharmacology 12/2008; 19(4):238-49. DOI:10.1016/j.euroneuro.2008.09.004 · 5.40 Impact Factor
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    • "The co-use of cocaine and heroin (commonly referred to as speedball; Ellinwood et al, 1976; DAWN database) is associated with an increased frequency of injection (Gleghorn et al, 1998; Colon et al, 2001), an increased transmission of bloodborne diseases such as HIV (Joe and Simpson, 1995; Irwin et al, 1996; Kral et al, 1998) and hepatitis C (Garfein et al, 1998; Thorpe et al, 2000; Miller et al, 2002), increased emergency room visits/overdose episodes (Ochoa et al, 2001; van Ameijden et al, 1999) relative to intravenous heroin use alone. This co-use has also been associated with decreased success rates in methadone maintenance program (Dunteman et al, 1992; Hartel et al, 1995; Saxon et al, 1996; Grella et al, 1997; Perez de los et al, 1997; Magura et al, 1998; Downey et al, 2000). Unfortunately, little is known about the environmental, behavioral, or biological factors that contribute to speedball use; however, anecdotal reports suggest that speedball 'feels better' than either drug alone (Kosten et al, 1988; Stine and Kosten, 1993). "
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    ABSTRACT: The co-use of cocaine and heroin is relatively common, with a growing clinical and preclinical literature dedicated to investigating the factors underlying the phenomenon. Specifically, several studies have compared the reinforcing effects of the coadministration of cocaine and heroin, referred to commonly as 'speedball', to either drug alone. The present study assessed whether addition of heroin to a wide range of cocaine doses produces reinforcing effects greater than cocaine alone using both a progressive ratio (PR) schedule and a choice procedure. Patterns of coadministration of cocaine and heroin offered simultaneously were also assessed using double-lumen cannulas. Under the PR schedule, speedball combinations across a range of doses (0.38-3.0 mg/kg/inf cocaine+1.5-48 microg/kg/inf heroin) did not support higher break points than cocaine alone. When cocaine and heroin were made available concurrently (ie on two separate levers), rats self-administered cocaine exclusively. Using a choice procedure, however, a preference was demonstrated for some speedball combinations (eg 0.18 mg/kg/inf cocaine+50 microg/kg/inf heroin; 0.38 mg/kg/inf cocaine+50 microg/kg/inf heroin) over cocaine alone (0.75 mg/kg/inf). So while results obtained using the PR schedule do not support the hypothesis that speedball combinations are more reinforcing than cocaine alone, data from the choice procedure do support this hypothesis. These apparently discrepant results demonstrate that these models are measuring different aspects of drug reinforcement, and suggest that choice procedures in rats provide a useful tool to study speedball self-administration.
    Neuropsychopharmacology 03/2005; 30(2):286-95. DOI:10.1038/sj.npp.1300560 · 7.83 Impact Factor
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