CBD Oil And Methadone

CBDISTILLERY

Buy CBD Oil Online

CBD Oil And Methadone The widespread use of heroin and prescription opioids in the United States during the past decade has resulted in an unprecedented epidemic of opioid addiction, and few Association between cannabis use and methadone maintenance treatment outcomes: an investigation into sex differences Open Access This article is distributed under the terms of the Creative Safety of Cannabidiol Given to Subject With Methadone or Buprenorphine The overarching goal of this study is to evaluate the potential of Cannabidiol (CBD) as an adjunctive treatment for comorbid

CBD Oil And Methadone

The widespread use of heroin and prescription opioids in the United States during the past decade has resulted in an unprecedented epidemic of opioid addiction, and few treatments for heroin use disorders are currently available. In this study, authors conducted a clinical trial to test whether cannabidiol (CBD), a non-intoxicating cannabinoid that is found in the cannabis plant, could reduce drug craving and anxiety in recently-abstinent individuals with heroin use disorder. The study found that, compared to those who received a placebo, individuals who received a dose of CBD medication showed a reduction in craving for heroin as well as reduced anxiety, which lasted for about a week after taking the CBD medication.

WHAT PROBLEM DOES THIS STUDY ADDRESS?

In the past decade, there has been an unprecedented spike in opioid use disorde r , which has led to more than 300,000 opioid-related deaths in the United States . O pioid use disorder medications such as methadone and buprenorphine (often prescribed in a formulation with naloxone , known by the brand name S uboxone ) help reduce opioid use and reduce risk for opioid-involved overdoses . In some areas, however, t hese medications are often underutilized and therefore can be difficult to access, creating a treatment gap in which those who need medications face barriers to actually receiving them. Further, 20-40% of opioid use disorder patients do not want to take agonist treatments .

One of the hypothesized factors contributing to these barriers is that methadone and Suboxone can be misused or diverted because they can produce euphoria . Consequently, discovering effective alternative medications that can also treat opioid use disorder that circumvent concerns about their psychoactive properties could help more of those affected . To address this problem , the authors investigated whether the cannabinoid , CBD , which is thought to be safe and non-addictive, could be useful in the treatment of opioid use disorder .

HOW WAS THIS STUDY CONDUCTED?

This was a randomized clinical trial with 42 participants who received one of two different CBD medication doses or a placebo once daily for 3 days and were then exposed to drug-related or neutral cues to see whether CBD could reduc e opioid cravings and anxiety – factors strongly associated with relapse to opioid use .

Participants were recruited through advertisements. Most participants indicated preference for intranasal heroin use, most reported currently using more than 10 bags of heroin (one bag = 1 g) daily, and on average, participants had been using heroin for over 10 years. The majority of participants (64.3%) had been abstinent from heroin use for less than 1 month.

The study medication used in this study, EPIDIOLEX, is a n FDA-approved medication that is dispensed through a pharmacy (not to be confused with “medical marijuana , ” which is comprised of a wide variety of non- federally- regulated cannabis projects ) . EPIDIOLEX is a plant-derived CBD liquid formation. P articipants were randomly assigned to receive 400 mg of CBD, 800 mg of CBD, or a placebo medication. CBD or placebo was administered once daily for 3 days . In addition to measuring the effect of the medication on opioid craving, anxiety, the authors also collected measures of positive and negative emotions, vital signs (skin temperature, blood pressure, heart rate, respiratory rate), and salivary cortisol levels , which measure stress response.

At three time points – immediately after the CBD or placebo administration ; 24 hours after the CBD or placebo administration ; and 7 days after the third and final CBD or placebo administration – p articipants were exposed to drug – related and neutral cues . The 3-minute neutral cue condition consisted of a video showing relaxing scenarios, such as scenes in nature. The drug cue condition was a 3-minute video that showed intravenous or intranasal drug use, depending on the participant’s reported preferred route of drug use . Immediately after the presentation of the videos , participants were also exposed to neutral objects or to heroin – related paraphernalia (e.g., syringe, rubber tie, and packets of powder resembling heroin) for 2 minutes. Authors examined whether patients who received CBD, compared to those who received placebo, showed differences in opioid craving, anxiety, positive and negative emotions, or vital signs , after being exposed to the drug or neutral cues.

WHAT DID THIS STUDY FIND?

I ndividuals receiving the non-psychoactive cannabinoid CBD medication reported less craving after being exposed to drug cues compared with i ndividuals receiving placebo . This effect lasted at least a week after the CBD or placebo administration, when i ndividuals receiving the high-dose of CBD (but not the low-dose) still reported less craving compared with those receiving placebo . In addition, CBD reduced measures of stress response after the drug cue – such as heart rate and salivary cortisol increases . I ndividuals receiving CBD reported less anxiety after being exposed to drug cues compared with i ndividuals receiving placebo (though t here w ere no significant difference s in anxiety between participants receiving the low-dose vs . the high-dose of CBD ) . There was no effect of CBD on positive affect or on any cognitive measures.

WHAT ARE THE IMPLICATIONS OF THE STUDY FINDINGS?

In light of the opioid epidemic, it is important to identify as many strategies as possible to curb opioid addiction. In the past few years, scientists have asked whether or not cannabis use can help individuals recover from opioid use disorder or may serve as a less-risky pain management approach to pharmaceutical opioids . Individuals also report using cannabinoids in an effort to cut back or quit other substances , but currently, data do not support this indication. Some studies have shown no benefit; in fact, studies have shown that cannabis use is related to greater odds of both new-onset opioid use and opioid use disorder 3 years later . The small, experimental study here shows a potential benefit of CBD in reduc ing cue-induced craving and anxiety in heroin-abstinent individuals . This suggest s a potential role for CBD in relapse prevention of heroin use disorder . T his study takes a more rigorous approach that can serve as a model for future studies of cannabinoids and their potential role in OUD treatment and recovery.

  1. The sample size in this study was very small and , although results are promising, the findings need replication in larger samples. The small sample also did not allow for exploration of sex/gender effects, which could be important given that women typically have higher craving and anxiety than men.
  2. The study medication used in this study, EPIDIOLEX, is a n FDA-approved medication that you can only get from a pharmacy. Though EPIDIOLEX is derived from cannabis, it is NOT medical marijuana . This medication does not contain THC, which is the compound in the cannabis plant that causes the ‘high’ and euphoria. It is therefore important for patients to realize that although benefits of CBD were found, this study does NOT support the use of “medical marijuana” for opioid use disorder.
  3. This study only examined opioid craving for 7 days. It is still unknown if CBD would reduce opioid craving past the 7-day window examined in this study o r whether use of CBD actually translates into less use of actual opioids.
  4. Patients in this study had to be abstinent from opioids, and not taking any agonist therapie s. Therefore, the population in this study r epresent s individuals who are doing well and may respond will to lots of different interventions . However, this population may not be representative of opioid use disorder patients more generally.
BOTTOM LINE
  • For individuals and families seeking recovery: This study showed that compared to placebo the non-psychoactive cannabinoid , CBD , was associated with substantially de creased cue-induced craving and anxiety for those with heroin use disorder . Many individuals with opioid use disorders are seeking alternative treatments to curb cravings and reduce anxiety, and many are reluctant to try agonist treatments such as methadone or suboxone . While more research is needed to flesh out whether CBD increase s the likelihood of long-term abstinence, this study suggests individuals may benefit from EPIDIOLEX, the FDA-approved CBD medication , but more larger studies are needed to confirm this . It is important to note, however, that individuals are using cannabis in its unregulated forms, and legislatures are passing med ical cannabis laws that identify opioid use disorder as one of the conditions for which cannabis is indicated without evidence to support this indication . Consequently, individuals seeking to use cannabis , in general, for opioid addiction should proceed cautiously .
  • Fortreatment professionals and treatment systems: This study showed that compared to placebo, CBD was associated with substantially de creased cue-induced craving and anxiety for those with heroin use disorder . A recent survey found that a considerable percentage (30%) of individuals receiving agonist treatment were worried about encountering negative attitudes related to being prescribed agonists, and only 33% reported their provider discussed this with them prior to attending a meeting . If CBD does pan out as a potential treatment of heroin use disorder, this could appeal to many p atient s, and could be a good complement to recovery support services. It is important for treatment professionals to be aware that the unregulated forms of cannabis, e.g. , those that can be purchased at medical marijuana dispensaries, are still unproven treatments, and may in fact produce more harm than good.
  • For scientists: This study showed that compared to placebo, CBD was associated with substantially de creased cue-induced craving and anxiety for those with heroin use disorder . More w ork is needed that more precisely measures whether CBD increases the likelihood of long-term abstinence , as well as for whom, and under what conditions , this medication work best. Greater knowledge in this regard could inform the nature of medication development more broadly . By pursuing investigation into other alternative treatments for opioid use disorder, scientists may be able to help reduce stigma and improve outcomes for patients with OUD .
  • For policy makers: This study showed that compared to placebo CBD was associated with substantially de creased cue-induced craving and anxiety for those with heroin use disorder . While more research is needed, CBD may be an alternative to other medications for opioid use disorder, which are limited and not well-accessible to racial/ethnic minorities and those without financial means . Policy makers, however, should be aware that this study does not provide evidence that unregulated forms of cannabis, especially those containing THC, help with OUD. F unding research studies that examine pure forms of CBD, and other alternative treatments for opioid use disorder , could help improve outcomes and reduce the public health burden of the current epidemic of opioid addiction .
CITATIONS

Hurd, Y. L., Spriggs, S., Alishayev , J., Winkel, G., Gurgov , K., Kudrich , C., . . . Salsitz , E. (2019). Cannabidiol for the reduction of cue-induced craving and anxiety in drug-abstinent individuals with heroin use disorder: A double-blind randomized placebo-controlled trial . American Journal of Psy chiatry, ( ePub ahead of print). doi : 10.1176/appi.ajp.2019.18101191

Association between cannabis use and methadone maintenance treatment outcomes: an investigation into sex differences

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Associated Data

The dataset for the current study is available from the corresponding author upon request.

Abstract

Background

Cannabis will soon become legalized in Canada, and it is currently unclear how this will impact public health. Methadone maintenance treatment (MMT) is the most common pharmacological treatment for opioid use disorder (OUD), and despite its documented effectiveness, a large number of patients respond poorly and experience relapse to illicit opioids. Some studies implicate cannabis use as a risk factor for poor MMT response. Although it is well established that substance-use behaviors differ by sex, few of these studies have considered sex as a potential moderator. The current study aims to investigate sex differences in the association between cannabis use and illicit opioid use in a cohort of MMT patients.

Methods

This multicentre study recruited participants on MMT for OUD from Canadian Addiction Treatment Centre sites in Ontario, Canada. Sex differences in the association between any cannabis use and illicit opioid use were investigated using multivariable logistic regression. A secondary analysis was conducted to investigate the association with heaviness of cannabis use.

Results

The study included 414 men and 363 women with OUD receiving MMT. Cannabis use was significantly associated with illicit opioid use in women only (OR = 1.82, 95% CI 1.18, 2.82, p = 0.007). Heaviness of cannabis use was not associated with illicit opioid use in men or women.

Conclusions

This is the largest study to date examining the association between cannabis use and illicit opioid use. Cannabis use may be a sex-specific predictor of poor response to MMT, such that women are more likely to use illicit opioids if they also use cannabis during treatment. Women may show improved treatment outcomes if cannabis use is addressed during MMT.

Background

Canada is currently developing legislation for the legalization of cannabis [1]. The rationale is that legalization would have social and economic advantages by generating revenue and deterring such crimes as illegal drug dealing [2]. Prohibition has been ineffective, with data suggesting that this policy option has created more societal costs by way of excessive incarceration, largely involving already marginalized individuals [3], and no evidence to suggest that these criminal penalties have any substantial effect on public health [4].

Colorado, USA, has recently legalized cannabis, and while it remains premature to assess the public health impact of this policy, data show that the commercialization of medical marijuana in 2009 led to a 20% increase in college age (18–25 years) monthly marijuana use and a 36% increase in adult (26+ years) monthly marijuana use in the following 3 years [5]. Legalizing cannabis will almost certainly increase its availability and accessibility; plausible mechanisms for increasing recreational use include reduced prices, ease of access, criminal penalties no longer acting as a deterrent, and increased social acceptability [6]. It is reasonable to expect that Canada will observe a similar increase in the prevalence of cannabis use, though its public health impact remains uncertain.

Despite the commonly held perception that cannabis is relatively harmless [7], its use has been linked to adverse consequences such as cognitive impairment, lower life satisfaction, respiratory problems, and increased risk of developing psychotic episodes and disorders [8]. Those with a history of psychiatric or substance-use disorders can experience worsened symptoms from cannabis use [1]. Cannabis users are also at heightened risk for developing other substance-use disorders [9]. However, the current system of criminalization is similarly associated with individual and public risks. For example, individuals with a criminal record from minor possession charges often experience considerable difficulties in finding employment or housing leading to further social and health risks [1]. Public costs of criminalization are also substantial, with an estimated $2.3 billion spent annually on enforcement and prosecution [1].

See also  Pure Spectrum CBD Oil

While public health risks of cannabis legalization may by and large be minimal, certain vulnerable populations are more susceptible to the deleterious effects of its use. One such population are those with substance-use disorders. North America is currently in the midst of an opioid crisis [10], in which we are witnessing a dramatic increase in non-medical use of opioids and subsequently the incidence of opioid use disorder (OUD). While opioid abuse is associated with serious adverse outcomes, it has been shown that the development of addiction is a major driver in the increase in opioid-related morbidity and mortality [11], indicating the extent to which OUD negatively impacts public health.

Because of the ongoing opioid epidemic in Canada, we must remain mindful of how increasing accessibility of cannabis will impact this population, in particular. Currently, the most commonly prescribed treatment for OUD is methadone maintenance treatment (MMT), an opioid substitution therapy [12]. MMT has proven to be effective in retaining patients in treatment and reducing opioid use and mortality [13], and this effectiveness has led to a steep increase in patients on MMT. In Ontario, Canada, the number of patients receiving MMT has nearly doubled since 2010 [12]. Despite its effectiveness, a significant number of patients respond poorly to treatment and experience relapse [14]. Illicit opioid use in combination with MMT is of immense concern, as it is a substantial risk factor for overdose and death [15].

Recent studies point to a changing landscape of OUD and those in treatment, one that includes a higher percentage of women, older aged patients, and more individuals abusing prescription opioids rather than heroin [16]. These sociodemographic changes warrant a re-evaluation of risk factors associated with poor MMT outcomes.

Compared to the general population, patients on MMT show a higher prevalence of cannabis use [16], and because of its documented association with polysubstance use [9, 17], psychiatric disorders [18], and overall worse quality of life [19], represents a potential risk factor for poor MMT outcomes. Several studies have investigated the influence of cannabis use on MMT outcomes in humans, though the results are mixed. Some studies have indicated cannabis use is associated with poorer treatment outcomes [20–22] while others looking at illicit opioid use found no significant association [23–26]. Although this is the case, confidence in these diverging results is reduced by methodological limitations such as small sample size and subjective outcome measures, making further investigations merited.

Furthermore, few studies have considered sex as a potential moderator. It is well established that substance-use behaviors differ by sex and different social and biological factors contribute to the development of substance-use disorders between men and women [27]. Although a higher proportion of men use cannabis, women who use cannabis are more likely to experience adverse outcomes such as development of cannabis use disorder, and may also be more likely to show negative outcomes from cannabis in other domains such as more severe cannabis withdrawal symptoms and [28] and worse mental health and social functioning [29]. A large survey of cannabis users, for example, found that a larger proportion of men use cannabis for recreational purposes while more women reported using it for purposes of self-medication [30]. Thus, motivational processes for drug use may differ between men and women.

The objective for this study is to investigate sex differences in the association between cannabis use and illicit opioid use during methadone maintenance treatment. We will build on previous research by including a large, representative sample of MMT patients to ensure adequate power and generalizability of findings. Our secondary objective is to determine whether heaviness of cannabis use is associated with illicit opioid use among male and female cannabis users.

Methods

Participants and procedure

Data were collected as part of the Genetics of Opioid Addiction (GENOA) program, an ongoing prospective cohort study conducted in collaboration with the Population Genomics Program at McMaster University, and the Canadian Addiction Treatment Centre (CATC) [31]. We recruited participants from 16 CATC sites across Ontario, Canada, from 2013 to 2016. Patients were eligible for participation if they were ≥18 years old, on methadone maintenance treatment for OUD, and able to provide informed written consent. Individuals were excluded if they did not speak English, were on an opioid substitution therapy other than methadone, or refused to provide blood or urine samples (Fig. 1 ). If individuals were deemed eligible for participation, they were provided with a written consent form to read and sign. Eligible participants provided informed written consent, upon which they underwent a face-to-face interview administered by trained research staff. Participants were compensated with a 5$ coffee shop gift card. This study was approved by the Hamilton Integrated Research Ethics Board (HIREB; Study ID 11-056).

Flow diagram for eligibility and screening of participants

Data collection

The study participants provided sociodemographic and clinical information during the face-to-face interview. Participants were asked to report their biological sex, and all participants reported either male or female. We also collected information regarding current methadone maintenance treatment, methadone dose, duration of current treatment, and information about any past treatments for opioid use disorder.

The Maudsley Addiction Profile (MAP) [32] was administered to retrieve information about substance-use, health risk behaviors, physical and psychological health, and personal and social functioning in the past 30 days. Substance-use data included information on number of days used in the past 30, typical dose used, and route of administration. We also used the physical and psychological health sections of the MAP to compare general health and well-being among participants. These sections comprised of eight questions each and were scored using a Likert scale ranging from 0 to 4 (never-always) to produce a maximum score of 40 per section.

All study data were collected and managed by trained researchers using REDCap electronic data capture tools [33].

Drug use measurements

In addition to self-reported use of drugs using the MAP, all study participants underwent routine weekly or biweekly urine toxicology screens at the clinical sites part of routine clinical care as per CATC management protocol.

Cannabis use

Cannabis use, the primary predictor variable, was measured using urinalysis (cut-off = 50 ng/ml for tetrahydrocannabinol) in the past 3 months. Unfortunately, several clinics discontinued screening for cannabis during urine testing, so only 45.0% of participants had any cannabis urine screens. Therefore, we opted to use self-reported cannabis use from the MAP. To verify the validity of self-reports, we calculated the sensitivity and specificity using participants who had data for both urinalysis and MAP (n = 349). The sensitivity was 79.9% (95% CI 72.7, 85.8) and specificity was 80.0% (95% CI 73.6, 85.4), and thus we deemed self-reported cannabis use an appropriate measure of cannabis use. Sensitivity and specificity values did not significantly differ between men and women, and there were no significant differences between false negatives and false positives.

For the primary regression analysis, we dichotomized cannabis use as any reported use versus no use in the past 30 days for our main predictor variable. We defined heaviness of cannabis use as the product of number of days used in the past 30 days by the typical dose per use (measured in grams) as reported on the MAP.

To quantify cannabis heaviness for participants who reported doses in values other than grams, we utilized the quantification of common “marijuana measurements” as determined and reported by Mariani et al. [34]. Many participants reported values such as “less than one joint” or “couple of puffs of a joint”, and we coded all of these reports as equivalent to one half of a joint (0.33 g). For all other reported quantities, we consulted an addiction expert to estimate the average dose per route of administration based on clinical experience. We used the following quantifications: bowl = 0.25 g and cookie = 2 g.

Illicit opioid use

Illicit opioid use during MMT was the primary outcome which was measured in the 3 months prior to baseline interview using urinalysis, with participants averaging 16 screens per 3 months. The cut-off concentration was 300 ng/mL for opiates and 100 ng/mL for oxycodone. We dichotomized illicit opioid use to reflect no positive screens versus any positive screens during a 3-month duration. This dichotomized variable is a patient-important treatment outcome, as the ultimate goal of MMT is complete abstinence of opioids. Individuals were excluded from analysis if they were currently prescribed any opioid medications, as these compromise the results of urine screens.

Statistical analysis

Descriptive statistics were reported to compare demographic characteristics between men and women. Continuous variables were expressed as mean (standard deviation) and categorical variables were expressed as number (percent). We employed a Student’s t test to test significant differences between continuous variables, and a chi-square test for categorical variables.

A multivariable logistic regression analysis was performed to investigate the association between cannabis and illicit opioid use, including an interaction term, sex by cannabis use, to investigate between-group sex differences. In the analysis, we controlled for age, sex, methadone dose, and treatment duration. Two multivariable logistic regression analyses were also performed for men and women separately to investigate within-group sex differences, controlling for the same covariates.

We conducted a secondary analysis on cannabis users to determine whether it is only the presence of cannabis use that influences treatment outcome or the heaviness of use that drives the association. For this, we replaced the binary cannabis variable with the continuous measurement of cannabis use heaviness. Multivariable logistic regression analyses were employed for male and female users, controlling for the same covariates as in the initial analysis.

Variables were assessed for collinearity using the variance inflation factor (VIF), and variables with VIF > 10 were excluded from the analysis. Adjusted odds ratios (OR), 95% confidence intervals (CI), and p values generated from the regression models are reported. The level of significance for hypothesis testing was set at alpha = 0.05 for the main analysis and alpha = 0.025 for analyses performed separately on men and women.

The general requirement for logistic regression is to have a minimum of 10 events per predictor variable [35]. We included 212 men and 183 women with the event (presence of at least one positive opioid urine screen), and we included four predictor variables therefore the study was adequately powered for analysis. When isolating cannabis users for the secondary analysis, there were 133 men and 91 women with the event, demonstrating adequate power.

All analyses were performed using IBM SPSS version 20. This study is reported in adherence to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [36].

Results

Participants’ characteristics

The total sample comprised of 777 participants including 414 men and 363 women (Fig. 1 ). Ages varied from 18 to 65 years with a mean age of 38.05 years (SD =11.11). The mean daily methadone dose was 75.44 mg (SD = 45.84), and the average duration of current MMT was 48.55 months (SD = 49.53).

Demographic and clinical characteristics comparing men and women are reported in Table 1 . 59.7 of males and 43.5% of females reported using cannabis. Furthermore, men on average used cannabis more often in the past 30 days and at a higher average dose. Women also had significantly worse physical and psychological functioning compared to men. A comparison of cannabis users and non-users can be found in Appendix 1.

Table 1

Demographic and clinical characteristics of men and women on MMT

Variable Men (n = 414) Women (n = 363) p value
Age in years (SD) 39.07 (11.72) 36.88 (10.27) 0.006
Ethnicity (% Caucasian) 347 (84.6%) 288 (80.2%) 0.127
Marital status
Never married (%) 203 (49.0%) 158 (43.5%) 0.079
Married/common law/living with partner (%) 129 (31.2%) 109 (30.0%)
Widowed/separated/divorced (%) 82 (19.8%) 96 (26.4%)
Education
Less than grade 9 (%) 88 (21.4%) 68 (18.9%) 0.008
Grade 9–12 (%) 233 (56.6%) 177 (49.2%)
Trade school, college, university (%) 91 (22.1%) 115 (31.9%)
Employment (% currently working) 175 (42.3%) 98 (27.0%)
Smoking status (% current smoker) 336 (81.2%) 320 (88.2%) 0.007
Age of onset of opioid use in years (SD) 24.90 (8.90) 25.00 (8.11) 0.881
Methadone dose in mg/day (SD) 78.15 (48.36) 72.34 (42.63) 0.079
Current treatment duration in years (SD) 4.10 (4.11) 3.98 (4.15) 0.704
Physical functioning (SD) 14.45 (7.74) 16.79 (7.38)
Psychological functioning (SD) 12.33 (8.82) 15.11 (9.36)
Cannabis use (% cannabis users) 247 (59.7%) 158 (43.5%)
Days cannabis use in last 30 (SD) 11.97 (13.54) 7.44 (12.02)
Average cannabis dose in g/day (SD) 1.48 (1.71) 1.04 (1.03) 0.004

Maximum score for the MAP physical and psychological functioning is 40, with higher scores indicating worse functioning

SD standard deviation

Cannabis use

The primary logistic regression analysis did not yield a significant association between cannabis use and illicit opioid use, after adjusting for age, sex, methadone dose, and treatment duration (OR = 1.16, 95% CI 0.77, 1.75, p = 0.49). The interaction of sex and cannabis use also did not show a significant association with illicit opioid use in the regression model (OR = 1.52, 95% CI 0.84, 2.77, p = 0.17) (Table ​ (Table2 2 ).

Table 2

Multivariable logistic regression analysis on predictors of illicit opioid use

Predictor Odds ratio 95% CI p value
Cannabis use 1.16 0.77–1.75 0.485
Sex*cannabis use 1.52 0.84–2.77 0.169
Age 1.00 0.99–1.02 0.857
Sex 0.83 0.54–1.28 0.399
Methadone dose 0.96* 0.93–0.99 0.023
Duration of treatment 0.91* 0.87–0.95

Age and duration of treatment interpreted as a one-point increase. Methadone dose interpreted as a 10-point increase

OR odds ratio, CI confidence interval

Sex differences

After adjusting for age, methadone dose, and treatment duration, any cannabis use in the past 30 days was significantly associated with illicit opioid use (OR = 1.82, 95% CI 1.18, 2.82, p = 0.007) in women but not in men (OR = 1.11, 95% CI 0.73, 1.69, p = 0.62) (Table 3 ).

Table 3

Multivariable logistic regression analysis on predictors of illicit opioid use by sex

Men Women
Predictor Odds ratio 95% CI p value Odds ratio 95% CI p value
Cannabis use 1.11 0.73–1.69 0.618 1.82* 1.18–2.82 0.007
Age 0.99 0.98–1.01 0.588 1.01 0.99–1.03 0.356
Methadone dose 0.94* 0.90–0.99 0.010 0.99 0.94–1.04 0.634
Duration of treatment 0.92* 0.87–0.97 0.004 0.90* 0. 84–0.95

Age and duration of treatment interpreted as a one-point increase. Methadone dose interpreted as a ten-point increase

OR odds ratio, CI confidence interval

Heaviness of cannabis use

Among cannabis users, the mean number of days of cannabis use in the past 30 days was 18.91 days (SD = 12.46) and the mean daily dose was 1.31 g (SD = 1.50), varying from 0.10 to 14.00 g. The logistic regression analysis showed the heaviness of cannabis use to be unrelated to illicit opioid use in both women (OR = 1.00, 95% CI 0.99, 1.01, p = 0.92) and men (OR = 1.01, 95% CI 1.00–1.01, p = 0.07) (Table 4 ).

Table 4

Multivariable logistic regression analysis on predictors of illicit opioid use among cannabis users by sex

Men Women
Predictor Odds ratio 95% CI p value Odds ratio 95% CI p value
Cannabis use heaviness 1.01 1.00–1.01 0.072 1.00 0.99–1.01 0.917
Age 0.99 0.97–1.02 0.476 1.02 0.98–1.05 0.449
Methadone dose 0.92* 0.87–0.98 0.016 1.02 0.94–1.11 0.662
Duration of treatment 0.91 0.84–0.99 0.037 0.91 0.83–0.99 0.035

Cannabis use heaviness, age, and duration of treatment interpreted as a one-point increase. Methadone dose interpreted as a 10-point increase

Discussion

The current study sought to investigate sex differences in the association between cannabis use and illicit opioid use in a cohort of MMT patients. Our results suggest that cannabis use during treatment may be a predictor of illicit opioid use in women. This could help explain why previous studies investigating this relationship provided conflicting results due to the lack of consideration of sex effect on the association between cannabis use and continued opioid use in MMT [23, 37].

To our knowledge, this is the largest study conducted to date investigating the relationship between cannabis use and illicit opioid use in men and women on MMT. While some studies have indicated that cannabis use is associated with poor MMT treatment outcomes [20–22], several previous studies looking at illicit opioid use have not found significant results [23, 24, 26]. These inconsistent reports could be explained by methodological limitations such as the selection of the study participants [23] and insufficient investigations into sex differences in cannabis use and MMT treatment outcomes. For example, the external validity of the studies reporting no association may be low, as two were secondary analyses of RCTs with restrictive inclusion criteria [23, 26], and one study analyzed a sample of predominantly men [24]. In this case, it is unlikely these findings apply to a current sample of MMT patients which contain about 50% women.

Despite the well-documented sex differences in the sociodemographic and clinical profiles of patients in MMT [38], there has been little research conducted on sex-specific predictors of MMT outcomes. Women are more sensitive to the subjective effects of cannabis (i.e., subjective ratings of intoxication and other drug effects like altered mood and sociability) and consequently show a faster trajectory to cannabis use disorder [28], indicating they may be have a higher proclivity to problematic cannabis use. Furthermore, cannabis use has consistently been shown to be associated with worse mental health outcomes in women compared to men [19, 39].

Preclinical research points to many important developmental and biological sex differences which suggest females are more susceptible to the deleterious effects of cannabis use. Studies in rodents have found that females exposed to ∆9-tetrahydrocannabinol (THC) were more susceptible to the reinforcing effects of cannabinoids, such that female rats more quickly acquired self-administration and were more sensitive to drug- and cue-induced reinstatement of the drug [40]. These behavioral observations may be explained by the findings that prolonged exposure to THC led to a much greater cannabinoid receptor desensitization in female rats compared to their male counterparts [40]. It was also found significantly greater concentrations of THC and its metabolites in the female rat brain compared to males [41]. Despite this evidence, there is a paucity of research looking into the sexually dimorphic effects of cannabis in humans [42].

While there is reason to consider biological mechanisms as explanation for the differential consequences of cannabis use in men and women, other clinical and social factors should not be overlooked. Women in MMT tend to show a higher prevalence of comorbid psychiatric and physical illnesses [16, 43, 44], as well as more severe opioid craving upon treatment entry [45] which may represent confounding factors that serve to increase rates of both cannabis and opioid use during MMT. As such, these patients may have motivation to use both drugs for purposes of self-medication. Indeed a survey of cannabis users found men were more likely to use cannabis recreationally while women were more likely to use it for purposes of self-medication for conditions such as anxiety and headaches [30]. As we only classified participants based on biological sex, further work should evaluate gender constructs and their influence on treatment response to determine whether the observed sex differences can be explained by biological or social mechanisms, or a combination of the two.

Unexpectedly, when looking at cannabis users only, we failed to find an association between heaviness of cannabis use and illicit opioid use in either sex. It is currently unclear why this is the case. A study by Saxon et al. [46] found that MMT patients who had intermittent positive cannabis urine screens had a significantly higher percentage of positive screens for other drugs of abuse compared to those who consistently had positive screens. Thus, the relationship between cannabis use heaviness and illicit opioid use may not be linear. On the other hand, this observation may simply be the result of our rough approximation of cannabis use heaviness and slang terminology reported in the interviews, rather than reflecting the true effect.

Several studies also indicate a distinct difference between recreational cannabis users and those with cannabis use disorder, regardless of frequency of use, such that patients with a cannabis use disorder actually show less polysubstance use during MMT [23, 47, 48]. It is unclear why this is the case, but it may represent a confounding effect such as having cannabis use disorder may be associated with lack of means to obtain further drugs and lack of will or time to use other drugs while on MMT. In this study, we did not find a significant association between the amount or frequency of cannabis use and illicit opioid use. However, our study lacks the ability to distinguish cannabis use disorder from recreational use.

Another consideration is to account for the potency of cannabis used by patients, which was not measured in this study. Research on opioid-dependent rats suggests cannabidiol (CBD) and THC, the two main active ingredients in cannabis, actually generate opposing response. Administration of CBD extinguishes cue-induced heroin-seeking behaviors following periods of abstinence [49], whereas THC administration seems to heighten opioid sensitivity and increase heroin self-administration [50, 51]. This antagonism is further supported by imaging studies in humans, which suggest that CBD attenuates the neurotoxic and adverse psychiatric effects of THC [52, 53]. Because of these differential effects, those who use cannabis for medicinal purposes may choose higher CBD concentrations while those who use it for recreational purposes may prefer greater amounts of THC. Therefore, depending on ratio of CBD to THC in the ingested cannabis, an individual may become more or less susceptible to further drug use, and this distinction should be investigated further.

Some limitations of this study should be noted. The cross-sectional nature of the analysis prevents any causal inferences from being made. Self-reported cannabis use, despite its adequate sensitivity and specificity may also be a biased estimate. Particularly in chronic cannabis users, short-term memory and recall may be impaired [54, 55] which could affect the accuracy of retrospective self-reports even further. Conversely, there is evidence to suggest self-report use may be a more valid and sensitive indicator of cannabis use compared to urine screening. For example, patients enrolled in methadone maintenance treatment are required to provide urine samples at least one or two times per week; however, studies have shown the average time for the first negative result in urine screening for THC metabolites following a single dose of THC was 8.5 days following ingestion for infrequent users and 19.1 days for chronic users [56]. This suggests that urine data may overestimate the frequency of cannabis use.

Conclusions

This study suggests that cannabis use is a potential sex-specific predictor of poor outcome during MMT. It will be important to look at the impact of cannabis use on women by systematically screening for cannabis use in women with OUD and providing addiction counseling to address not only opioid use but also cannabis use in this vulnerable group. This study also showed that women with OUD experienced physical and psychological symptoms more frequently than men; these symptoms may be the underlying cause of cannabis use in women in this study and addiction services should consider sex-specific treatment programs to manage symptoms and co-substance use.

Acknowledgements

The authors would like to extend their gratitude to Jackie Hudson and Sheelagh Rutherford for their ongoing dedication and contributions to GENOA. We would like to thank the CATC staff and management for their collaboration with this research project, as well as all the GENOA team members for their valuable contributions and expertise that made this project possible. We would also like to acknowledge all students who helped out with data collection, entry, and management for this project. Finally, we would like to thank the study participants who generously volunteered their time and data, without which, none of this would be possible.

Funding

This work was supported by the Canadian Institute for Health Research, the Chanchlani Research Centre, and Peter Boris Centre for Addictions Research. The funding agencies had no role in the design of the study, review process, or publication of results.

Availability of data and materials

The dataset for the current study is available from the corresponding author upon request.

Authors’ contributions

LZ was responsible for conception and design of the study, acquisition of data, analysis and interpretation of data, manuscript writing, and critical revision of the manuscript. MB and NS contributed to acquisition of data, manuscript writing, and critical revision of the manuscript. CP, AW, MV, JD, GP, DM, and DD were responsible for data collection, communication with CATC clinics, and critical revision of the manuscript. JM, MS, and SM were responsible for analysis and interpretation of data, and critical revision of the manuscript. LT assisted with statistical analysis and critical revision of the manuscript. ZS contributed to the conception and design of the study, analysis and interpretation of data, and critical revision of the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publications

Ethics approval and consent to participate

This study was approved by the Hamilton Integrated Research Ethics Board (HIREB; Study ID 11-056). All participants in this study provided informed written consent.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abbreviations

CATC Canadian Addiction Treatment Centre
CBD Cannabidiol
CI Confidence interval
GENOA Genetics of Opioid Addiction
HIREB Hamilton Integrated Research Ethics Board
MAP Maudsley Addiction Profile
MMT Methadone maintenance treatment
OR Odds ratio
OUD Opioid use disorder
SD Standard deviation
STROBE Strengthening the reporting of observational studies in epidemiology
THC ∆9-tetrahydrocannabinol
VIF Variance inflation factor

Appendix 1

Table 5

Demographic and clinical characteristics of cannabis users and non-users on MMT

Variable Cannabis non-users (n = 372) Cannabis users (n = 405) p value
Age in years (SD) 39.78 (11.05) 36.46 (10.94)
Sex (% female) 205 (55.1%) 158 (39.0%)
Ethnicity (% Caucasian) 306 (83.4%) 329 (81.8%) 0.634
Marital status
Never married (%) 150 (40.3%) 211 (52.1%) 0.004
Married/common law/living with partner (%) 126 (33.9%) 112 (27.7%)
Widowed/separated/divorced (%) 96 (25.8%) 82 (20.2%)
Education
Less than grade 9 (%) 67 (18.2%) 89 (22.0%) 0.087
Grade 9–12 (%) 190 (51.6%) 220 (54.5%)
Trade school, college, university (%) 111 (30.2%) 95 (23.5%)
Employment (% currently working) 132 (35.5%) 141 (34.8%) 0.880
Smoking status (% current smoker) 301 (80.9%) 355 (87.7%) 0.010
Age of onset of opioid use in years (SD) 26.12 (9.08) 23.86 (7.86)
Methadone dose in mg per day (SD) 78.77 (46.54) 72.36 (45.02) 0.053
Current treatment duration in years (SD) 4.26 (4.35) 3.85 (3.91) 0.164
Physical functioning (SD) 15.06 (7.92) 16.02 (7.38) 0.085
Psychological functioning (SD) 12.90 (9.57) 14.27 (8.76) 0.040

Maximum score for the MAP physical and psychological functioning is 40, with higher scores indicating worse functioning

SD standard deviation

Contributor Information

Zainab Samaan, Phone: 905 522 1155, Email: [email protected] .

References

1. Task Force on Marijuana Legalization and Regulation. Toward the legalization, regulation and restriction of access to marijuana: discussion paper. 2016.

2. Hajizadeh M. Legalizing and regulating marijuana in Canada: review of potential economic, social, and health impacts. Int J Heal Policy Manag. 2016; 5 :453–6. doi: 10.15171/ijhpm.2016.63. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

3. Rehm J, Fischer B. Cannabis legalization with strict regulation, the overall superior policy option for public health. Clin Pharmacol Ther. 2015; 97 :541–4. doi: 10.1002/cpt.93. [PubMed] [CrossRef] [Google Scholar]

4. Room R, Reuter P. How well do international drug conventions protect public health? Lancet. 2012; 379 :84–91. doi: 10.1016/S0140-6736(11)61423-2. [PubMed] [CrossRef] [Google Scholar]

5. Rocky Mountain High Intensity Drug Trafficking Area. The legalization of marijuana in Colorado: the impact. 2014.

6. Hall W, Lynskey M. Evaluating the public health impacts of legalizing recreational cannabis use in the United States. Addiction. 2016; 111 :1764–73. doi: 10.1111/add.13428. [PubMed] [CrossRef] [Google Scholar]

7. Porath-Waller A, Brown J, Frigon AP, Clark H. What Canadian youth think about cannabis [Internet]. Can. Cent. Subst. Abus. 2013;1-57. Available from: http://www.ccsa.ca/Resource%20Library/CCSA-What-Canadian-Youth-Think-about-Cannabis-2013-en.pdf.

8. Volkow ND, Baler RD, Compton WM, Weiss SRB. Adverse health effects of marijuana use. N Engl J Med. 2014; 370 :2219–27. doi: 10.1056/NEJMra1402309. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

9. Blanco C, Hasin DS, Wall MM, Flórez-Salamanca L, Hoertel N, Wang S, et al. Cannabis use and risk of psychiatric disorders: prospective evidence from a US national longitudinal study. JAMA Psychiat. 2016;73:1–8. [PubMed]

10. Nelson LS, Juurlink DN, Perrone J. Addressing the opioid epidemic. JAMA. 2015; 314 :1453–4. doi: 10.1001/jama.2015.12397. [PubMed] [CrossRef] [Google Scholar]

11. Kolodny A, Courtwright DT, Hwang CS, Kreiner P, Eadie JL, Clark TW, et al. The prescription opioid and heroin crisis: a public health approach to an epidemic of addiction. Annu Rev Public Health. 2015; 36 :559–74. doi: 10.1146/annurev-publhealth-031914-122957. [PubMed] [CrossRef] [Google Scholar]

12. Fischer B, Kurdyak P, Goldner E, Tyndall M, Rehm J. Treatment of prescription opioid disorders in Canada: looking at the “other epidemic”? Subst Abuse Treat Prev Policy. 2016;11:1-4. [PMC free article] [PubMed]

13. Mattick RP, Breen C, Kimber J, Davoli M. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev. 2009;3:CD002209. [PMC free article] [PubMed]

14. Lions C, Carrieri MP, Michel L, Mora M, Marcellin F, Morel A, et al. Predictors of non-prescribed opioid use after one year of methadone treatment: an attributable-risk approach (ANRS-methaville trial) Drug Alcohol Depend. 2014; 135 :1–8. doi: 10.1016/j.drugalcdep.2013.10.018. [PubMed] [CrossRef] [Google Scholar]

15. Bohnert ASB, Ilgen MA, Trafton JA, Kerns RD, Eisenberg A, Ganoczy D, et al. Trends and regional variation in opioid overdose mortality among Veterans Health Administration patients, fiscal year 2001 to 2009. Clin J Pain. 2014;30:605–12. [PubMed]

16. Bawor M, Dennis BB, Varenbut M, Daiter J, Marsh DC, Plater C, et al. Sex differences in substance use, health, and social functioning among opioid users receiving methadone treatment: a multicenter cohort study. Biol Sex Differ. 2015; 6 :21. doi: 10.1186/s13293-015-0038-6. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

17. Degenhardt L, Hall W, Lynskey M. The relationship between cannabis use and other substance use in the general population. Drug Alcohol Depend. 2001; 64 :319–27. doi: 10.1016/S0376-8716(01)00130-2. [PubMed] [CrossRef] [Google Scholar]

18. Moore THM, Zammit S, Lingford-Hughes A, Barnes TRE, Jones PB, Burke M, et al. Cannabis use and risk of psychotic or affective mental health outcomes: a systematic review. Lancet. 2007; 370 :319–28. doi: 10.1016/S0140-6736(07)61162-3. [PubMed] [CrossRef] [Google Scholar]

19. Lev-Ran S, Imtiaz S, Taylor BJ, Shield KD, Rehm J, Le Foll B. Gender differences in health-related quality of life among cannabis users: results from the national epidemiologic survey on alcohol and related conditions. Drug Alcohol Depend. 2012; 123 :190–200. doi: 10.1016/j.drugalcdep.2011.11.010. [PubMed] [CrossRef] [Google Scholar]

20. Wasserman DA, Weinstein MG, Havassy BE, Hall SM. Factors associated with lapses to heroin use during methadone maintenance. Drug Alcohol Depend. 1998; 52 :183–92. doi: 10.1016/S0376-8716(98)00092-1. [PubMed] [CrossRef] [Google Scholar]

21. Proctor SL, Copeland AL, Kopak AM, Hoffmann NG, Herschman PL, Polukhina N. Outcome predictors for patients receiving methadone maintenance treatment: findings from a retrospective multi-site study. J Subst Use. 2016;21:1–13.

22. Roux P, Carrieri PM, Cohen J, Ravaux I, Spire B, Gossop M, et al. Non-medical use of opioids among HIV-infected opioid dependent individuals on opioid maintenance treatment: the need for a more comprehensive approach. Harm Reduct J. 2011; 8 :31. doi: 10.1186/1477-7517-8-31. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

23. Epstein DH, Preston KL. Does cannabis use predict poor outcome for heroin-dependent patients on maintenance treatment? Past findings and more evidence against. Addiction. 2003; 98 :269–79. doi: 10.1046/j.1360-0443.2003.00310.x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

24. Nirenberg TD, Cellucci T, Liepman MR, Swift RM, Sirota AD. Cannabis versus other illicit drug use among methadone maintenance patients. Psychol Addict Behav. 1996; 10 :222–7. doi: 10.1037/0893-164X.10.4.222. [CrossRef] [Google Scholar]

25. Calsyn DA, Saxon AJ. An innovative approach to reducing cannabis use in a subset of methadone maintenance clients. Drug Alcohol Depend. 1999; 53 :167–9. doi: 10.1016/S0376-8716(98)00121-5. [PubMed] [CrossRef] [Google Scholar]

26. Saxon AJ, Wells EA, Fleming C, Jackson TR, Calsyn DA. Pre-treatment characteristics, program philosophy and level of ancillary services as predictors of methadone maintenance treatment outcome. Addiction. 1996; 91 :1197–209. doi: 10.1046/j.1360-0443.1996.918119711.x. [PubMed] [CrossRef] [Google Scholar]

27. Fattore L, Melis M, Fadda P, Fratta W. Sex differences in addictive disorders. Front Neuroendocrinol. 2014; 35 :272–84. doi: 10.1016/j.yfrne.2014.04.003. [PubMed] [CrossRef] [Google Scholar]

28. Cooper ZD, Haney M. Investigation of sex-dependent effects of cannabis in daily cannabis smokers. Drug Alcohol Depend. 2014; 136 :85–91. doi: 10.1016/j.drugalcdep.2013.12.013. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

29. Aspis I, Feingold D, Weiser M, Rehm J, Shoval G, Lev-Ran S. Cannabis use and mental health-related quality of life among individuals with depressive disorders. Psychiatry Res. 2015; 230 :341–9. doi: 10.1016/j.psychres.2015.09.014. [PubMed] [CrossRef] [Google Scholar]

30. Cuttler C, Mischley LK, Sexton M. Sex differences in cannabis use and effects: a cross-sectional survey of cannabis users. Cannabis Cannabinoid Res. 2016; 1 :166–75. doi: 10.1089/can.2016.0010. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

31. Samaan Z, Bawor M, Dennis BB, Plater C, Varenbut M, Daiter J, et al. Genetic influence on methadone treatment outcomes in patients undergoing methadone maintenance treatment for opioid addiction: a pilot study. Neuropsychiatr Dis Treat. 2014; 10 :1503–8. doi: 10.2147/NDT.S66234. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

32. Marsden J, Gossop M, Stewart D, Best D, Farrell M, Strang J. The Maudsley Addiction Profile Development and User manual. Natl. Addict. Centre/Institute Psychiatry. 1998; 1–40.

33. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009; 42 :377–81. doi: 10.1016/j.jbi.2008.08.010. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

34. Mariani JJ, Brooks D, Haney M, Levin FR. Quantification and comparison of marijuana smoking practices: blunts, joints, and pipes. Drug Alcohol Depend. 2011; 113 :249–51. doi: 10.1016/j.drugalcdep.2010.08.008. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

35. Peduzzi P, Concato J, Kemper E, Holford TR, Feinstem AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996; 49 :1373–9. doi: 10.1016/S0895-4356(96)00236-3. [PubMed] [CrossRef] [Google Scholar]

36. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61:344–9. [PubMed]

37. Scavone JL, Sterling RC, Weinstein SP, Van Bockstaele EJ. Impact of cannabis use during stabilization on methadone maintenance treatment. Am J Addict. 2013; 22 :344–51. doi: 10.1111/j.1521-0391.2013.12044.x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

38. Bawor M, Dennis BB, Bhalerao A, Plater C, Worster A, Varenbut M, et al.. Sex differences in outcomes of methadone maintenance treatment for opioid addiction: a systematic review and meta-analysis. C. Open. 2015;3:E344-E351. [PMC free article] [PubMed]

39. van Gastel WA, MacCabe JH, Schubart CD, van Otterdijk E, Kahn RS, Boks MPM. Cannabis use is a better indicator of poor mental health in women than in men: a cross-sectional study in young adults from the general population. Community Ment Health J. 2014;50:823–30. [PubMed]

40. Craft RM, Marusich JA, Wiley JL. Sex differences in cannabinoid pharmacology: a reflection of differences in the endocannabinoid system? Life Sci. 2013; 92 :476–81. doi: 10.1016/j.lfs.2012.06.009. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

41. Tseng AH, Harding JW, Craft RM. Pharmacokinetic factors in sex differences in ∆9- tetrahydrocannabinol-induced behavioral effects in rats. Behav Brain Res. 2004; 154 :77–83. doi: 10.1016/j.bbr.2004.01.029. [PubMed] [CrossRef] [Google Scholar]

42. Fattore L. Considering gender in cannabinoid research: a step towards personalized treatment of marijuana addicts. Drug Test Anal. 2013; 5 :57–61. doi: 10.1002/dta.1401. [PubMed] [CrossRef] [Google Scholar]

43. Evans E, Kelleghan A, Li L, Min J, Huang D, Urada D, et al. Gender differences in mortality among treated opioid dependent patients. Drug Alcohol Depend. 2015; 155 :228–35. doi: 10.1016/j.drugalcdep.2015.07.010. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

44. Peles E, Schreiber S, Naumovsky Y, Adelson M. Depression in methadone maintenance treatment patients: rate and risk factors. J Affect Disord. 2007; 99 :213–20. doi: 10.1016/j.jad.2006.09.017. [PubMed] [CrossRef] [Google Scholar]

45. Back SE, Payne RL, Wahlquist AH, Carter RE, Stroud Z, Haynes L, et al. Comparative profiles of men and women with opioid dependence: results from a national multisite effectiveness trial. Am J Drug Alcohol Abuse. 2011; 37 :313–23. doi: 10.3109/00952990.2011.596982. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

46. Saxon AJ, Calsyn DA, Greenberg D, Blaes P, Haver VM, Stanton V. Urine screening for marijuana among methadone-maintained patients. Am J Addict. 1993; 2 :207–11. doi: 10.1111/j.1521-0391.1993.tb00421.x. [CrossRef] [Google Scholar]

47. Peirce JM, Petry NM, Roll JM, Kolodner K, Krasnansky J, Stabile PQ, et al. Correlates of stimulant treatment outcome across treatment modalities. Am J Drug Alcohol Abuse. 2009; 35 :48–53. doi: 10.1080/00952990802455444. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

48. Best D, Gossop M, Greenwood J, Marsden J, Lehmann P, Strang J. Cannabis use in relation to illicit drug use and health problems among opiate misusers in treatment. Drug Alcohol Rev. 1999; 18 :31–8. doi: 10.1080/09595239996734. [CrossRef] [Google Scholar]

49. Ren Y, Whittard J, Higuera-Matas A, Morris CV, Hurd YL. Cannabidiol, a nonpsychotropic component of cannabis, inhibits cue-induced heroin-seeking and normalizes discrete mesolimbic neuronal disturbances. J Neurosci. 2009;29:14764–9. [PMC free article] [PubMed]

50. Ellgren M, Spano SM, Hurd YL. Adolescent cannabis exposure alters opiate intake and opioid limbic neuronal populations in adult rats. Neuropsychopharmacology. 2007; 32 :607–15. doi: 10.1038/sj.npp.1301127. [PubMed] [CrossRef] [Google Scholar]

51. Solinas M, Panlilio LV, Goldberg SR. Exposure to delta-9-tetrahydrocannabinol (THC) increases subsequent heroin taking but not heroin’s reinforcing efficacy: a self-administration study in rats. Neuropsychopharmacology. 2004; 29 :1301–11. doi: 10.1038/sj.npp.1300431. [PubMed] [CrossRef] [Google Scholar]

52. Demirakca T, Sartorius A, Ende G, Meyer N, Welzel H, Skopp G, et al. Diminished gray matter in the hippocampus of cannabis users: Possible protective effects of cannabidiol. Drug Alcohol Depend. 2011; 114 :242–5. [PubMed] [Google Scholar]

53. Schubart CD, Sommer IEC, van Gastel WA, Goetgebuer RL, Kahn RS, Boks MPM. Cannabis with high cannabidiol content is associated with fewer psychotic experiences. Schizophr Res. 2011; 130 :216–21. doi: 10.1016/j.schres.2011.04.017. [PubMed] [CrossRef] [Google Scholar]

54. Volkow ND, Swanson JM, Evins AE, DeLisi LE, Meier MH, Gonzalez R, et al. Effects of cannabis use on human behavior, including cognition, motivation, and psychosis: a review. JAMA Psychiatry. 2016;73:292-97. [PubMed]

55. Crane NA, Schuster RM, Fusar-Poli P, Gonzalez R. Effects of cannabis on neurocognitive functioning: recent advances, neurodevelopmental influences, and sex differences. Neuropsychol Rev. 2013; 23 :117–37. doi: 10.1007/s11065-012-9222-1. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

56. Grotenhermen F. Pharmacokinetics and pharmacodynamics of cannabinoids. Clin Pharmacokinet. 2003; 42 :327–60. doi: 10.2165/00003088-200342040-00003. [PubMed] [CrossRef] [Google Scholar]

Safety of Cannabidiol Given to Subject With Methadone or Buprenorphine

The overarching goal of this study is to evaluate the potential of Cannabidiol (CBD) as an adjunctive treatment for comorbid opioid use disorder (OUD) and chronic pain. This is a randomized, placebo-controlled, crossover human laboratory study investigating the dose-dependent safety and acute effects of CBD on measures of pain and opioid craving in outpatients with OUD receiving medication-assisted treatment (MAT) with methadone or buprenorphine.

Condition or disease Intervention/treatment Phase
Addiction Drug: CBD Day 1 Drug: CBD Day 2 Drug: CBD Day 3 Early Phase 1

An initial safety pilot phase will recruit six participants: three receiving treatment with methadone and three receiving treatment with buprenorphine. If the results of the pilot study support the safety of CBD administration in this clinical sample, the general study will recruit 48 participants with comorbid OUD and chronic pain, for a total of 24 completers – 12 subjects (6 men and 6 women) receiving methadone and 12 subjects (6 men and 6 women) receiving buprenorphine. Both sub-studies will enroll participants who do not currently require an inpatient hospitalization.

Layout table for study information

Study Type : Interventional (Clinical Trial)
Estimated Enrollment : 6 participants
Allocation: Non-Randomized
Intervention Model: Crossover Assignment
Intervention Model Description: Initial safety pilot phase of 6 participants,(3 methadone and 3 on Buprenorphine) The general study is a randomized, placebo-controlled, crossover human laboratory study investigating the dose-dependent safety and acute effects of CBD on measures of pain and opioid craving in outpatients with OUD receiving medication-assisted treatment (MAT) with methadone or buprenorphine.
Masking: None (Open Label)
Primary Purpose: Treatment
Official Title: Cannabidiol Pharmacotherapy for Comorbid Opioid Addiction and Chronic Pain
Actual Study Start Date : December 8, 2021
Estimated Primary Completion Date : April 30, 2023
Estimated Study Completion Date : July 30, 2023
    Pain Threshold [ Time Frame: 4 measurements per test day, 3 total test days ]

The Cold Pressor (CPT measures Pain threshold (in seconds). For this test, a cooler filled with cold water (32.9-34.7degrees F/0.5-1.5 degrees C) are used. Participants are instructed to immerse their hand into the water and report the first time they experience pain (pain threshold). Lower scores indicate lower pain threshold. Minimum score is 0 seconds, and a maximum cut-off score of 300 seconds is used to prevent tissue damage.

The Cold Pressor Test (CPT) measures pain threshold and pain tolerance (in seconds). For this test, a water cooler is filled with cold water (32.9-34.7ºF/0.5-1.5ºC) are used. To begin the CPT, Participants are then instructed to immerse their hand into the cold water bath and report when the pain becomes unbearable (pain tolerance). Lower scores indicate lower pain tolerance. Minimum score is 0 seconds, and a maximum cut-off score of 300 seconds is used to prevent tissue damage.

The QST is a reliable, dynamic, and computerized method of quantifying distinct mechanisms of the pain experience

The QST is a reliable, dynamic, and computerized method of quantifying distinct mechanisms of the pain experience

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.

Layout table for eligibility information

Ages Eligible for Study: 18 Years to 70 Years (Adult, Older Adult)
Sexes Eligible for Study: All
Accepts Healthy Volunteers: No
  • Males and females, Veterans and non-Veterans, aged between 18 and 70 years old.
  • Diagnosed with OUD and currently enrolled in methadone or buprenorphine maintenance treatment.
  • Having chronic pain, uniformly operationalized as grade II (high-intensity) non- cancer pain for ≥ 6 months 49.
  • Capable of providing informed consent in English.
  • Compliant in opioid maintenance treatment and on a stable dose for four weeks or longer.
  • Not meeting DSM-5 criteria for substance use disorders other than OUD or tobacco use disorder within the last 12 months.
  • No current medical problems deemed contraindicated for participation by principal investigator.
  • For women, not pregnant as determined by pregnancy screening; not breast-feeding; using acceptable birth control methods. Acceptable contraception for females includes oral contraceptives, contraceptive depot injections, contraceptive subdermal implants, intrauterine devices, or surgical contraception methods. Acceptable contraception for males includes condoms or surgical contraception methods.
  • Other current major psychiatric disorders deemed clinically unstable by the principal investigator, such as severe depression and/or active suicidal ideation.
  • Having experienced major psychosocial stressors recently (≤ 6 weeks before enrollment), at the discretion of the principal investigator.
  • Methadone dose under 60mg or over 100mg
  • Buprenorphine over 24mg.
  • Having received inpatient psychiatric treatment recently (≤ 60 days before enrollment).
  • Candidates receiving products containing either THC or CBD will be excluded.
  • Current use regular use other prescription opioids, gabapentinoids (pregabalin, gabapentin), antidepressants (SSRIs, SNRIs, TCAs), benzodiazepines, platelet inhibitors (e.g., clopidogrel, apixaban, ticagrelor), or NSAIDs.
  • Current weight of less of 60 kg.
  • Allergy to sesame seed oil, which is an ingredient of the CBD formulation used.
  • Serious medical or neurological illness or treatment for a medical disorder that could interfere with study participation as determined by principal investigator.
  • Participants who have elevation of liver enzymes (ALT and/or AST) 2x above the normal limit or higher.

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05076370

How useful was this post?

Click on a star to rate it!

Average rating 3 / 5. Vote count: 1

No votes so far! Be the first to rate this post.