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Background: Craving is a core clinical feature of cannabis use disorder (CUD) and a predictor of treatment outcomes, yet its temporal course during treatment is not well characterized. This study aimed to identify latent classes of cannabis craving trajectories among adults with CUD and examine associated baseline predictors and cannabis use outcomes.

Methods: This was a secondary analysis of the National Drug Abuse Treatment Clinical Trials Network’s CTN-0053 trial, a 12-week, multisite randomized controlled trial of N-acetylcysteine versus placebo for adults with CUD (N = 302). Cannabis craving was measured using the Marijuana Craving Questionnaire–Short Form at six treatment timepoints (weeks 1–5, 9 and 12) and one 5-week post-treatment follow-up (week 17). Urine cannabinoid tests were conducted twice weekly throughout treatment and follow-up. Latent class growth analysis identified craving trajectories. The present study aimed to identify latent classes of cannabis craving over 12 weeks of treatment and examine baseline predictors of class membership.

Results: A four-class solution provided the best fit: low craving (41%), moderate-decreasing craving (38%), moderate-stable craving (11%), and high craving (10%). Participants in higher craving classes exhibited greater baseline anxiety, depression, and obsessive-compulsive symptoms related to cannabis use. The high craving class had the greatest proportion of cannabis positive urine tests (96%) and the lowest urine test completion rate.

Conclusions: Craving follows heterogeneous trajectories during CUD treatment and is associated with co-occurring mental health symptoms and poorer outcomes. Dynamic craving assessment may support personalized treatment and strategies to prevent return to use.

Related protocols: CTN-0053

High levels of missing outcome data for biologically confirmed substance use (BCSU) threaten the validity of substance use disorder (SUD) clinical trials. Underlying attributes of clinical trials could explain BCSU missingness and identify targets for improved trial design.

We reviewed 21 clinical trials funded by the NIDA National Drug Abuse Treatment Clinical Trials Network (CTN) and published from 2005 to 2018 that examined pharmacologic and psychosocial interventions for SUD. We used configurational analysis-a Boolean algebra approach that identifies an attribute or combination of attributes predictive of an outcome-to identify trial design features and participant characteristics associated with high levels of BCSU missingness. Associations were identified by configuration complexity, consistency, coverage, and robustness. We limited results using a consistency threshold of 0.75 and summarized model fit using the product of consistency and coverage.

For trial design features, the final solution consisted of two pathways: psychosocial treatment as a trial intervention OR larger trial arm size (complexity=2, consistency=0.79, coverage=0.93, robustness score=0.71). For participant characteristics, the final solution consisted of two pathways: interventions targeting individuals with poly- or nonspecific substance use OR younger age (complexity=2, consistency=0.75, coverage=0.86, robustness score=1.00).

Conclusions: Psychosocial treatments, larger trial arm size, interventions targeting individuals with poly- or nonspecific substance use, and younger age among trial participants were predictive of missing BCSU data in SUD clinical trials. Interventions to mitigate missing data that focus on these attributes may reduce threats to validity and improve utility of SUD clinical trials.

Related protocols: CTN-0002, CTN-0003, CTN-0004, CTN-0006, CTN-0007, CTN-0009. CTN-0013, CTN-0014, CTN-0015, CTN-0017, CTN-0021, CTN-0029, CTN-0030, CTN-0031, CTN-0037, CTN-0044, CTN-0046, CTN-0048, CTN-0051, CTN-0053

Suicide is the tenth leading cause of death in the United States and continues to be a major public health concern. Suicide risk is highly prevalent among individuals with co-occurring substance use disorders (SUD) and mental health disorders, making them more prone to adverse substance use related outcomes including overdose. Identifying individuals with SUD who are suicidal, and therefore potentially most at risk of overdose, is an important step to address the synergistic epidemics of suicides and overdose fatalities in the United States. The current study assesses whether patterns of suicidality endorsement can indicate risk for substance use and overdose.

Latent class analysis (LCA) was used to assess patterns of item level responses to the Concise Health Risk Tracking Self-Report (CHRT-SR), which measures thoughts and feelings associated with suicidal propensity. We used data from 2,541 participants with SUD who were enrolled across 8 randomized clinical trials in the National Drug Abuse Treatment Clinical Trials Network from 2012 to 2021 (CTN-0037, -0049, -0051, -0053, -0054, -0064, -0067, -0068). Characteristics of individuals in each class were assessed, and multivariable logistic regression was performed to examine class membership as a predictor of overdose. LCA was also used to analyze predictors of substance use days.

Three classes were identified and discussed: Class (1) Minimal Suicidality, with low probabilities of endorsing each CHRT-SR construct; Class (2) Moderate Suicidality, with high probabilities of endorsing pessimism, helplessness, and lack of social support, but minimal endorsement of despair or suicidal thoughts; and Class (3) High Suicidality with high probabilities of endorsing all constructs. Individuals in the High Suicidality class comprise the highest proportions of males, Black/African American individuals, and those with a psychiatric history and baseline depression, as compared with the other two classes. Regression analysis revealed that those in the High Suicidality class are more likely to overdose as compared to those in the Minimal Suicidality class (p = 0.04).

Conclusions: Suicidality is an essential factor to consider when building strategies to screen, identify, and address individuals at risk for overdose. The integration of detailed suicide assessment and suicide risk reduction is a potential solution to help prevent suicide and overdose among people with SUD.

Related protocols: CTN-0037, CTN-0049, CTN-0051, CTN-0053, CTN-0054, CTN-0064, CTN-0067, CTN-0068

Treatments for cannabis use disorder (CUD) have limited efficacy and little is known about who responds to existing treatments. Accurately predicting who will respond to treatment can improve clinical decision-making by allowing clinicians to offer the most appropriate level and type of care. This study aimed to determine whether multivariable/machine learning models can be used to classify CUD treatment responders vs. non-responders.

This secondary analysis used data from National Drug Abuse Treatment Clinical Trials Network (NIDA CTN) multi-site outpatient clinical trial (CTN-0053, Achieving Cannabis Cessation – Evaluating N-Acetylcysteine Treatment (ACCENT)). Adults with CUD (N=302) received 12 weeks of contingency management, brief cessation counseling, and were randomized to receive additionally either 1) N-Acetylcysteine or 2) placebo. Multivariable/machine learning models were used to classify treatment responders (i.e., two consecutive negative urine cannabinoid tests or a 50% reduction in days of use) versus non-responders using baseline demographic, medical, psychiatric, and substance use information.

Prediction performance for various machine learning and regression prediction models yielded area under the curves (AUCs) greater than 0.70 for four models (0.72-0.77), with support vector machine models having the highest overall accuracy (73%; 95% confidence interval [CI]: 68-78%) and AUC (0.77; 95% CI: 0.72, 0.83). Fourteen variables were retained in at least 3 of 4 top models, including demographic (ethnicity, education), medical (diastolic/systolic blood pressure, overall health, neurological diagnosis), psychiatric (depressive symptoms, generalized anxiety disorder, antisocial personality disorder), and substance use (tobacco smoker, baseline cannabinoid level, amphetamine use, age of experimentation with other substances, cannabis withdrawal intensity) characteristics.

Conclusions: Multivariable/machine learning models can improve upon chance prediction of treatment response to outpatient cannabis use disorder treatment, though further improvements in prediction performance are likely necessary for decisions about clinical care.

Related protocols: CTN-0053

Increasing rates of overdose and overdose deaths are a significant public health problem. Research has examined co-occurring mental health conditions, including suicidality, as a risk factor for intentional and unintentional overdose among individuals with substance use disorder (SUD). However, this research has been limited to single site studies of self-reported outcomes.

The current research evaluated suicidality as a predictor of overdose events in 2541 participants who use substances enrolled across eight multi-site clinical trials completed within the National Drug Abuse Treatment Clinical Trials Network between 2012 to 2021 (CTN-0037, -0049, -0051, -0053, -0054, -0064, -0067, and -0068). The trials assessed baseline suicidality with the Concise Health Risk Tracking Self-Report (CHRT-SR). Overdose events were determined by reports of adverse events, cause of death, or hospitalization due to substance overdose, and verified through a rigorous adjudication process. Multivariate logistic regression was performed to assess continuous CHRT-SR score as a predictor of overdose, controlling for covariates.

CHRT-SR score was associated with overdose events (p=0.03) during the trial; the likelihood of overdose increased as continuous CHRT score increased (OR 1.02). Participants with lifetime heroin use were more likely to overdose (OR 3.08).

Conclusions: Response to the marked rise in overdose deaths should integrate suicide risk reduction as part of prevention strategies.

Related protocols: CTN-0037, CTN-0049, CTN-0051, CTN-0053, CTN-0054, CTN-0064, CTN-0067, CTN-0068

There are a wide variety of methods for using combustible cannabis which may impact an individual’s pattern of use as well as their response to cannabis use disorder (CUD) treatment. Previous research has noted racial/ethnic differences in cannabis users’ preferred method of use.

This study examined data from a randomized placebo-controlled trial of a pharmacological intervention for adults with CUD (CTN-0053). Latent profile analysis classified participants (N=302) based on their primary method of combustible cannabis use.

A four profile solution emerged that identified participants who demonstrated 1) Primarily Joint (n=50), 2) Primary Blunt (n=106), 3) Mixed Method of Use (MoU; n=30), and 4) Primarily Pipe (i.e. pipe or bong; n=116) use. Profiles were compared on socio-demographic characteristics and racial differences were found among the four latent profiles as well as differences in their level of use. Cannabis users with a preference for joints were more likely to be White as compared to other racial groups. In contrast, a greater proportion of participants with a preference for blunts were African American. The Primarily Joint profile was found to have the highest cannabis relapse rate at 1-month follow-up (94%) which was significantly greater than the Mixed MoU (74%) and Primarily Pipe (78%) profiles. Interestingly, there was no difference in 1-month follow-up cannabis relapse rates between the Primarily Joint and Primarily Blunt profiles (87%).

Conclusions: Findings suggest that treatment-seeking individuals who primarily use joints or blunts may face unique challenges that may impact cannabis abstinence. Along with other cannabis-related characteristics, an individual’s preferred method of use may represent an important factor to consider in the treatment of CUD.

Related protocols: CTN-0053

This study, part of CTN-0053, evaluated the associations between regular cannabis use, with and without tobacco co-use, and cardiovascular outcomes.

Using electronic health records, control patients, with no cannabis-use-documentation, were matched to the cannabis-using patients on demographics, residential zip code median income, body mass index, and, for the total sample, tobacco use disorder (TUD) status. Outcomes were encounter diagnosis (yes/no) of cerebrovascular accident (CVA), heart arrhythmia, myocardial infarction, subarachnoid hemorrhage (SAH), and all-cause mortality.

TUD-patients had the greatest prevalence of cardiovascular disease, regardless of cannabis-use indication. In the total sample and non-TUD subgroup, regular cannabis use was significantly associated with greater risk for CVA, arrhythmia, SAH, and mortality. In the TUD subgroup, regular cannabis use was significantly associated with greater risk for arrhythmia and SAH.

Conclusions: Cannabis use is associated with significantly greater risk of adverse cardiovascular diagnoses and overall death, particularly in non-tobacco users.

Related protocols: CTN-0053

Depression is common among individuals with cannabis use disorder (CUD), particularly those who present for CUD treatment. Treatments that consider this comorbidity are essential.

The goal of this secondary analysis was to examine whether N-acetylcysteine (NAC) reduced depressive symptoms among adults (age 8-50) with CUD (N=302) and whether the effect of NAC on cannabis cessation varied as a result of baseline levels of depression. Bidirectional associations between cannabis use amount and depression were also examined.

Data for the analysis were from a NIDA Clinical Trials Network multi-site clinical trial for CUD (CTN-0053). Adults with CUD (N=302) were randomized to receive 2400mg of NAC daily or matched placebo for 12 weeks. All participants received abstinence-based contingency management. Cannabis quantity was measured by self-report, and weekly urinary cannabinoid levels (11-nor-9-carboxy- 9-tetrahydrocannabinol) confirmed abstinence. Depressive symptoms were measured by the Hospital Anxiety and Depression Scale.

Results found that depressive symptoms did not differ between the NAC and placebo groups during treatment. There was no significant interaction between treatment and baseline depression predicting cannabis abstinence during treatment. Higher baseline depression was associated with decreased abstinence throughout treatment and a significant gender interaction suggested that they may be particularly true for females. Cross-lagged panel models suggested that depressive symptoms preceded increased cannabis use amounts (in grams) during the subsequent month. The reverse pathway was not significant (i.e., greater cannabis use preceding depressive symptoms).

Conclusions: Results from this study indicate that symptoms of depression may be a barrier to cannabis cessation among adults, regardless of whether NAC is administered. Overall, the findings suggest that depressive symptoms should be considered clinically relevant within cannabis cessation programs for adults, and that more research is needed to explore treatments that could mitigate the impact of depressive symptoms on treatment outcomes. Treatments that address depressive symptoms concurrently with CUD treatment may be particularly beneficial.

Related protocols: CTN-0053

Despite the high prevalence of blunt smoking among cannabis users, very few studies examine the clinical profile of blunt smokers relative to those using more common methods of cannabis use, like joints.

This study uses baseline data from the ACCENT study (Achieving Cannabis Cessation – Evaluating N-acetylcysteine Treatment, CTN-0053), a multi-site randomized pharmacotherapy clinical trial within the NIDA Clinical Trials Network, to predict the association between blunt and joint use frequency and cannabis use characteristics (e.g., grams of cannabis used) and consequences (e.g., withdrawal) among past-month cannabis users (N=377) who were screen for study participation.

After controlling for race, age, gender, other forms of cannabis use (including joint use) and nicotine dependence, multivariable linear regression models indicated that the number of days of blunt use in the past month was a significant predictor of the average amount of cannabis per using day, the estimated average cost of cannabis, and Cannabis Withdrawal scores. Frequency of joint use did not significantly predict any of the cannabis use characteristics or consequences.

Conclusions: Blunt smokers may present to treatment with greater amounts of cannabis smoked and more intense withdrawal symptoms, which may adversely impact their likelihood of successful abstinence. Cannabis-dependent blunt smokers may be more likely to benefit from treatment that targets physiological and mood-related withdrawal symptoms.

Related protocols: CTN-0053

It is common for cannabis users to also use tobacco. While data suggest that tobacco users have more difficulty achieving cannabis cessation, secondary analyses of clinical trial data sets may provide insight into the moderating variables contributing to this relationship, as well as changes in tobacco use during cannabis treatment. Those were the aims of this secondary analysis.

The parent study, CTN-0053, was a multi-site trial of N-acetylcysteine (NAC) for cannabis dependence conducted within the National Drug Abuse Treatment Clinical Trials Network. Participants were treatment-seeking adults (ages 18–50) who met criteria for cannabis dependence (N=302). For cigarette smokers (n=117), tobacco use was assessed via timeline follow-back and nicotine dependence was assessed via the Fagerström Test for Nicotine Dependence (FTND). Outcome measures included: 1) changes in tobacco use based on treatment assignment, nicotine dependence, and concurrent cannabis reduction/abstinence, and 2) independent associations between nicotine dependence and cannabis abstinence.

Analysis found that cigarette smokers accounted for 39% of the sample (117/302), with a median FTND score of 3.0 (10-point scale). Among those with lower baseline nicotine dependence scores, cigarette smoking was reduced in the active treatment group compared to placebo. Those with moderate/high levels of nicotine dependence showed slight increases in smoking following active treatment. Nicotine dependence did not affect cannabis cessation.

Conclusions: Cigarette smoking during cannabis treatment was affected, but depended on baseline nicotine dependence severity, though dependence levels did not impact cannabis abstinence. Interventions that address both tobacco and cannabis are needed, especially due to an increasing prevalence of cannabis use.

Related protocols: CTN-0053

Individuals with alcohol use disorder (AUD) do not always respond to currently available treatments, and evaluation of new candidate pharmacotherapies is indicated. N-acetylcysteine (NAC), an over-the-counter supplement, has shown promise in treating a variety of substance use disorders, but little research has evaluated its merits as a treatment for AUD. This secondary analysis of data from NIDA Clinical Trials Network protocol CTN-0053 examined the effects of NAC versus placebo on alcohol use among participants with cannabis use disorder (CUD) enrolled in a 12-week, multi-site cannabis cessation trial.

Participants (N=302, ages 18-50) were randomized to double-blind NAC (1200mg, twice daily) or placebo. Neither alcohol use nor desire for alcohol cessation were requirements for participation. Participants that returned for at least one treatment visit and had recorded alcohol use data (i.e., total drinks per week, drinking days per week, and binge drinking days per week) were included in the analysis (n=277).

Results found that participants in the NAC group, compared to the placebo group, had increased odds of between-visit alcohol abstinence, fewer drinks per week, and fewer drinking days per week. The increase in odds of complete abstinence from alcohol was 37% in the NAC group. The NAC group was 33% less likely to increase their number of drinks, compared to the placebo group, and their drinking days were 31% less than those in the placebo group as well. NAC did not affect the number of binge drinking days, however participants were binge drinking, on average, less than one time per month, so a significant decrease may be hard to detect in this sample. Age, sex, and race did not affect findings.

Conclusions: Though the original study found that NAC was not efficacious in reducing cannabis use in an adult sample, this secondary analysis suggests that NAC may be effective at reducing consumption of alcohol by approximately 30% among treatment-seeking adults with CUD, suggesting a need for further trials focused on the effects of NAC on alcohol consumption among individuals seeking treatment for AUD.

Related protocols: CTN-0053

The agreement between self-reported cannabis abstinence with urine cannabinoid concentrations in a clinical trials setting is not well characterized. This study assessed the agreement between various cannabinoid cutoffs and self-reported abstinence across three clinical trials, one including contingency management for abstinence. All three of the trials included both participant self-report and weekly urine samples for cannabis and creatinine concentration measurements. Bootstrapped data were assessed for agreement between self-reported 7+ day abstinence and urine cannabinoid tests using generalized linear mixed effects models for clustered binary outcomes. One study implemented contingency management for cannabis abstinence. Four hundred and seventy-three participants with 3787 valid urine specimens were included. Urine was analyzed for 11-nor-9-carboxy-delta-9-tetrahydrocannabinol and creatinine using immunoassay methods Biological cutoffs of 50, 100, and 200 ng/ml, as well as changes in CN normalized THCCOOH (25%/50% decrease), were assessed for agreement with self-reported abstinence during the three clinical trials.

Results found that agreement between measured THCCOOH and self-reported abstinence increases with increasing cutoff concentrations, while the agreement with self-reported non-abstinence decreases with increasing cutoff concentrations. Combining THCCOOH cutoffs with recent changes in CN-THCCOOH provides a better agreement in those self-reporting abstinence. Participants in the studies that received CM for abstinence had a lower agreement between self-reported abstinence and return to use than those in studies that did not have a contingency management component.

Conclusions: Using a combination of both concurrent THCCOOH and recent changes in CN-THCCOOH, the agreement between self-reported cannabis abstinence initiation and measure agreement is shortened significantly.

Related protocols: CTN-0053

Quantifying cannabis use is complex due to a lack of a standardized packaging system that contains specified amounts of constituents. A laboratory procedure has been developed for estimating physical quantity of cannabis use by utilizing a surrogate substance to represent cannabis, and weighing the amount of the surrogate to determine typical use in grams. This secondary analysis used data from a multi-site, randomized, controlled pharmacological trial for adult cannabis use disorder (N=300), sponsored by the National Drug Abuse Treatment Clinical Trials Network (protocol CTN-0053), to test the incremental validity of this procedure. In conjunction with the Timeline Followback, this physical scale-based procedure was used to determine whether average grams per cannabis administration predicted urine cannabinoid levels (11-nor-9-carboxy-delta-9-tetrahydrocannabinol) and problems due to use, after accounting for self-reported number of days use (in the past 30 days) and number of administrations per day in a 12-week clinical trial for cannabis use disorder.

Likelihood ratio tests suggest that model fit was significantly improved when grams per administration and relevant interactions were included in the model predicting urine cannabinoid level and in the model predicting problems due to cannabis use, relative to a model that contained only simpler measures of quantity and frequency.

Conclusions: This study provides support for the use of a scale-based method for quantifying cannabis use in grams. This methodology may be useful when precise quantification is necessary, for example, for researchers to begin to establish meaningful cut-offs for high-risk cannabis use. Researchers may use grams per episode to determine clinical cut-offs for high-risk episodic use in terms of “standard joints,” similar to cut-offs developed in the alcohol literature. Precise quantification of cannabis use also offers some advantages over urine cannabinoid biomarker data, as it can be adapted for remote data collection and is better suited to detect variability in use patterns.

Related protocols: CTN-0053

This is the primary outcomes article for CTN-0053.

Cannabis use disorder (CUD) is a prevalent and impairing condition, and established psychosocial treatments convey limited efficacy. In light of recent findings supporting the efficacy of N-acetylcysteine (NAC) for CUD in adolescents, the objective of this trial was to evaluate its efficacy in adults. In a 12-week double-blind randomized placebo-controlled trial, treatment-seeking adults ages 18-50 with CUD (N=302), enrolled across six NIDA Clinical Trials Network-affiliated clinical sites, were randomized in a 1:1 ratio to a 12-week course of NAC 1200 mg (n=153) or placebo (n=149) twice daily. All participants received contingency management (CM) and medical management. The primary efficacy measure was the odds of negative urine cannabinoid tests during treatment, compared between NAC and placebo participants.

Results found not-statistically-significant evidence that the NAC and placebo groups differed in cannabis abstinence (odds ratio=1.00, 95% confidence interval 0.63-1.59; p=0.984). Overall, 22.3% of urine cannabinoid tests in the NAC group were negative, compared with 22.4% in the placebo group. Many participants were medication non-adherent; however, exploratory analysis within the medication-adherent subgroups revealed no significant differential abstinence outcomes by treatment group.

Conclusions: In contrast with significant prior findings in adolescents, there is no evidence that NAC 1200mg twice daily plus CM is differentially efficacious for CUD in adults when compared to placebo plus CM. This discrepant finding between adolescents and adults with CUD may have been influenced by differences in development, cannabis use profiles, responses to embedded behavioral treatment, medication adherence, and other factors. In light of these findings, a replication trial of NAC in adolescents with CUD is indicated.

Related protocols: CTN-0053

This study examined the longitudinal association between reductions in cannabis use and changes in anxiety, depression, sleep quality, and quality of life. Secondary analyses were conducted based on data from a cannabis use disorder medication trial in 302 adults, NIDA Clinical Trials Network protocol CTN-0053, Achieving Cannabis Cessation: Evaluating N-Acetylcysteine Treatment (ACCENT). Changes in symptoms of anxiety and depression, sleep quality, and quality of life were assessed in relation to changes in cannabis use during the 12-week trial of treatment.

Based on the slope of individual cannabis use trajectory, the sample was classified into two groups (Cannabis Use Reduction, n=152 vs. Cannabis Use Increase, n=150) which was included as a binary covariate in subsequent modeling. Controlling for demographics (age, gender, race/ethnicity), treatment condition, and time-varying tobacco and alcohol use, separate latent growth curve models showed a significant association between the Cannabis Use Reduction group and improvement (i.e., lower values in slope) in anxiety, depression, and sleep quality over the observation period, but not in quality of life.

Conclusions: These results indicate a longitudinal relationship between reductions in cannabis use and improvements in anxiety, depression, and sleep quality. Clinicians treating patients with co-occurring cannabis use and problems with anxiety, depression, or sleep quality should attend to cannabis use reduction as a component of treatment.

Related protocols: CTN-0053