RESUMO

Background: The relationship between cannabis use and the risk of returning to using opioids non-medically during treatment for opioid use disorder (OUD) remains unclear.Objective: We sought to quantify the impact of cannabis use on the risk of non-medical opioid use among people receiving pharmacotherapies for OUD.Methods: A comprehensive search was performed using multiple databases from March 1 to April 5 of 2023. Eligible studies longitudinally assessed the association between cannabis use and non-medical opioid use among people with OUD receiving treatment with buprenorphine, methadone, or naltrexone. We utilized a random-effects model employing the restricted maximum likelihood method. A sensitivity analysis was conducted to understand potential differences between each OUD treatment modality.Results: A total of 10 studies were included in the final meta-analysis. There were 8,367 participants (38% female). The average follow-up time across these studies was 9.7 months (SD = 3.77), ranging from 4 to 15 months. The pharmacotherapies involved were methadone (76.3%) buprenorphine (21.3%), and naltrexone (2.4%). The pooled odds ratio did not indicate that cannabis use significantly influenced non-medical opioid use (OR: 1.00, 95% CI: 0.97-1.04, p = .98). There is evidence of moderate heterogeneity and publication bias.Conclusion: There was no significant association between cannabis use and non-medical opioid use among patients receiving pharmacotherapies for OUD. These findings neither confirm concerns about cannabis increasing non-medical opioid use during MOUD, nor do they endorse its efficacy in decreasing non-medical opioid use with MOUD. This indicates a need for individualized approaches for cannabis use and challenges the requirement of cannabis abstinence to maintain OUD pharmacotherapies.

Assuntos

Buprenorfina , Metadona , Naltrexona , Tratamento de Substituição de Opiáceos , Transtornos Relacionados ao Uso de Opioides , Humanos , Transtornos Relacionados ao Uso de Opioides/tratamento farmacológico , Naltrexona/uso terapêutico , Buprenorfina/uso terapêutico , Tratamento de Substituição de Opiáceos/métodos , Metadona/uso terapêutico , Estudos Longitudinais , Analgésicos Opioides/uso terapêutico

RESUMO

BACKGROUND: cocaine craving is a core feature of cocaine use disorder and remains a critical challenge for abstinence and relapse prevention. This review summarizes the anti-craving efficacy of pharmacotherapies tested for cocaine use disorder, in the context of randomized-controlled clinical trials. OBJECTIVES: we assessed the databases of the U.S. National Library of Medicine, Google Scholar, and PsycINFO, without date restrictions up to August 2022, to identify relevant studies. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS: we included double-blinded randomized-controlled trials investigating pharmacotherapies for cocaine craving and/or cocaine use disorder whose outcomes included cocaine craving. STUDY APPRAISAL AND SYNTHESIS METHODS: Two authors screened studies' titles and abstracts for inclusion, and both read all the included studies. We systematically gathered information on the following aspects of each study: title; author(s); year of publication; sample size; mean age; sample characteristics; study set-ting; whether participants were treatment-seeking; study design; craving measures; study interventions; drop-out rates; and other relevant outcomes. RESULTS: Overall, we appraised 130 clinical trials, including 8137 participants. We further considered the drugs from the studies that scored equal to or greater than six points in the quality assessment. There was a correlation between craving and cocaine use outcomes (self-reports, timeline follow-back or urinary benzoylecgonine) in the vast majority of studies. In the short-term treatment, acute phenylalanine-tyrosine depletion, clonidine, fenfluramine, meta-chlorophenylpiperazine (m-CPP) and mecamylamine presented promising effects. In the long term, amphetamine, biperiden, carbamazepine, lisdexamfetamine, lorcaserin, methamphetamine, mirtazapine, pioglitazone, progesterone, guanfacine, levodopa, nefazodone presented promising anti-craving effects. Unfortunately, the highly tested medications were not successful in most of the trials, as follows: propranolol in the short term; amantadine, aripiprazole, bromocriptine, citicoline, ketamine, modafinil, olanzapine, topiramate in the long term. The remaining 52 medications had no positive anti-craving outcomes. LIMITATIONS: Our review was limited by high heterogeneity of craving assessments across the studies and by a great range of pharmacotherapies. Further, the majority of the studies considered abstinence and retention in treatment as the main outcomes, whereas craving was a secondary outcome and some of the studies evaluated patients with cocaine use disorder with comorbidities such as opioid or alcohol use disorder, schizophrenia, bipolar disorder or attention deficit hyperactivity. Lastly, most of the studies also included non-pharmacological treatments, such as counseling or psychotherapy. CONCLUSIONS: There is a direct association between craving and cocaine use, underscoring craving as an important treatment target for promoting abstinence among persons with cocaine use disorder. Clonidine, fenfluramine and m-CPP showed to be promising medications for cocaine craving in the short-term treatment, and amphetamine, biperiden, carbamazepine, lisdexamfetamine, lorcaserin, methamphetamine, mirtazapine, pioglitazone, progesterone, guanfacine, levodopa, nefazodone in the long-term treatment.

RESUMO

BACKGROUND: Although Alcohol Use Disorder (AUD) is highly prevalent worldwide, treating this condition remains challenging. Further, potential treatments for AUD do not fully address alcohol-induced neuroadaptive changes. Understanding the effects of pharmacotherapies for AUD on the human brain may lead to tailored, more effective treatments, and improved individual clinical outcomes. OBJECTIVES: We systematically reviewed the literature for studies investigating pharmacotherapies for AUD that included neuroimaging-based treatment outcomes. We searched the PubMed, Scielo, and PsycINFO databases up to January 2021. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS: Eligible studies included those investigating pharmacotherapies for AUD and employing functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single-photon emission computed tomography (SPECT), and/or proton magnetic resonance spectroscopy (H-MRS). STUDY APPRAISAL AND SYNTHESIS METHODS: Two independent reviewers screened studies' titles and abstracts for inclusion. Data extraction forms were shared among all the authors to standardize data collection. We gathered information on the following variables: sample size; mean age; sociodemographic and clinical characteristics; alcohol use status; study design and methodology; main neuroimaging findings and brain-regions of interest (i.e., brain areas activated by alcohol use and possible pharmacological interactions); and limitations of each study. RESULTS: Out of 177 studies selected, 20 studies provided relevant data for the research topic. Findings indicate that: (1) Acamprosate and gabapentin may selectively modulate limbic regions and the anterior cingulate cortex; (2) Naltrexone and disulfiram effects may involve prefrontal, premotor, and cerebellar regions; (3) Pharmacotherapies acting on glutamate and GABA neurotransmission involve primarily areas underpinning reward and negative affective states, and; (4) Pharmacotherapies acting on opioid and dopamine systems may affect areas responsible for the cognitive and motor factors of AUD. LIMITATIONS: Most of the studies were focused on naltrexone. A small number of studies investigated the action of disulfiram and gabapentin, and no neuroimaging studies investigated topiramate. In addition, the time between medication and neuroimaging scans varied widely across studies. CONCLUSIONS: We identified key-brain regions modulated by treatments available for AUD. Some of the regions modulated by naltrexone are not specific to the brain reward system, such as the parahippocampal gyrus (temporal lobe), parietal and occipital lobes. Other treatments also modulate not specific regions of the reward system, but play a role in the addictive behaviors, including the insula and dorsolateral prefrontal cortex. The role of these brain regions in mediating the AUD pharmacotherapy response warrants investigation in future research studies.