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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

The prevalence of cannabis use disorder (CUD) is increasing in the US and primary care providers need tools to identify patients with moderate-severe CUD to facilitate treatment. A single-item screen for cannabis (SIS-C) has outstanding discriminative validity for CUD. However, because the prevalence of moderate-severe CUD is typically low, the probability that an average patient who screens positive for daily cannabis has moderate-severe cannabis use disorder is low, making follow-up assessment important.

This study, part of CTN-0077-Ot, reports the discriminative validity of a DSM-5 Substance Use Symptom Checklist (“Checklist”) for moderate-severe CUD among 498 primary care patients who reported daily cannabis use on the SIS-C. We evaluated the performance of the Checklist (score 0–11) completed during routine care, compared to =4 DSM-5 CUD symptoms (moderate-severe CUD) on the Composite International Diagnostic Interview Substance Abuse Module from a confidential survey (reference standard). We estimated areas under receiver operating curve (AUROC), sensitivities, specificities, and post-test probabilities.

Of 498 eligible patients, 17% met diagnostic criteria for moderate-severe CUD. The Checklist’s AUROC for moderate-severe CUD was 0.77 (95% CI: 0.71–0.83), and Checklist scores of 1–2 balanced sensitivity and specificity. Among patients from a population with average prevalence of CUD before screening (~6% prevalence) and daily use on the SIS-C, a Checklist score of 3 indicated a post-test probability of 82.1%.

Conclusions: Overall performance of the Checklist was good and the high specificity made it useful for identifying patients likely to have moderate-severe CUD among those at average risk.

Related protocols: CTN-0077-Ot

Medical cannabis is commonly used for chronic pain, but little is known about differences in characteristics, cannabis use patterns, and perceived helpfulness among primary care patients who use cannabis for pain versus nonpain reasons.

Among 1688 patients who completed a 2019 cannabis survey administered in a health system in Washington state, where recreational use is legal, participants who used cannabis for pain (n = 375) were compared with those who used cannabis for other reasons (n = 558) using survey and electronic health record data. We described group differences in participant characteristics, use patterns, and perceptions and applied adjusted multinomial logistic and modified Poisson regression.

Participants who used cannabis for pain were significantly more likely to report using applied (50.7% vs 10.6%) and beverage cannabis products (19.2% vs 11.6%), more frequent use (47.1% vs 33.1% for use =2 times per day; 81.6% vs 69.7% for use 4 to 7 days per week), and smoking tobacco cigarettes (19.2% vs 12.2%) than those who used cannabis for other reasons. They were also significantly more likely to perceive cannabis as very/extremely helpful (80.5% vs 72.7%), and significantly less likely to use cannabis for nonmedical reasons (4.8% vs 58.8%) or report cannabis use disorder symptoms (51.7% vs 61.1%).

Conclusions: Primary care patients who use cannabis for pain use it more frequently, often in applied and ingested forms, and have more co-use of tobacco, which may differentially impact safety and effectiveness. These findings suggest the need for different approaches to counseling in clinical care.

Related protocols: CTN-0077-Ot

Medical and nonmedical cannabis use and cannabis use disorders (CUD) have increased with increasing cannabis legalization. However, the prevalence of CUD among primary care patients who use cannabis for medical or nonmedical reasons is unknown for patients in states with legal recreational use.

The goal of this study, a secondary analysis of data from CTN-0077-Ot, was to estimate the prevalence and severity of CUD among patients who report medical use only, nonmedical use only, and both reasons for cannabis use in a state with legal recreational use.

This cross-sectional survey study took place at an integrated health system in Washington State. Among 108 950 adult patients who completed routine cannabis screening from March 2019 to September 2019, 5000 were selected for a confidential cannabis survey using stratified random sampling for frequency of past-year cannabis use and race and ethnicity. Among 1688 respondents, 1463 reporting past 30-day cannabis use were included in the study.

Patient responses to the Composite International Diagnostic Interview-Substance Abuse Module for CUD, corresponding to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition CUD severity (0-11 symptoms) were categorized as any CUD (=2 symptoms) and moderate to severe CUD (=4 symptoms). Adjusted analyses were weighted for survey stratification and nonresponse for primary care population estimates and compared prevalence of CUD across reasons for cannabis use.

Of 1463 included primary care patients (weighted mean [SD] age, 47.4 [16.8] years; 748 [weighted proportion, 61.9%] female) who used cannabis, 42.4% (95% CI, 31.2%-54.3%) reported medical use only, 25.1% (95% CI, 17.8%-34.2%) nonmedical use only, and 32.5% (95% CI, 25.3%-40.8%) both reasons for use. The prevalence of CUD was 21.3% (95% CI, 15.4%-28.6%) and did not vary across groups. The prevalence of moderate to severe CUD was 6.5% (95% CI, 5.0%-8.6%) and differed across groups: 1.3% (95% CI, 0.0%-2.8%) for medical use, 7.2% (95% CI, 3.9%-10.4%) for nonmedical use, and 7.5% (95% CI, 5.7%-9.4%) for both reasons for use (P=.01).

Conclusions: In this cross-sectional study of primary care patients in a state with legal recreational cannabis use, CUD was common among patients who used cannabis. Moderate to severe CUD was more prevalent among patients who reported any nonmedical use. These results underscore the importance of assessing patient cannabis use and CUD symptoms in medical settings.

Related protocols: CTN-0077-Ot

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

Cannabis use is prevalent and increasing, and frequent use intensifies the risk of cannabis use disorder (CUD). CUD is underrecognized in medical settings, but a validated single-item cannabis screen could increase recognition.

The purpose of this study was to evaluate the Single-Item Screen-Cannabis (SIS-C), administered and documented in routine primary care, compared with a confidential reference standard measure of CUD. This diagnostic study included a sample of adult patients who completed routine cannabis screening between January 28 and September 12, 2019, and were randomly selected for a confidential survey about cannabis use. Random sampling was stratified by frequency of past-year use and race and ethnicity. The study was conducted at an integrated health system in Washington state, where adult cannabis use is legal. Data were analyzed from May 2021 to March 2022.

The SIS-C asks about frequency of past-year cannabis use with responses (none, less than monthly, monthly, weekly, daily or almost daily) documented in patients’ medical records. The Diagnostic and Statistical Manual, Fifth Edition (DSM-5) Composite International Diagnostic Interview–Substance Abuse Module (CIDI-SAM) for past-year CUD was completed on a confidential survey and considered the reference standard. The SIS-C was compared with 2 or more criteria on the CIDI-SAM, consistent with CUD. All analyses were weighted, accounting for survey design and nonresponse, to obtain estimates representative of the health system primary care population.

Of 5000 sampled adult patients, 1688 responded to the cannabis survey (34% response rate). Patients were predominantly middle-aged (weighted mean [SD] age, 50.7 [18.1]), female or women (weighted proportion [SE], 55.9% [4.1]), non-Hispanic (weighted proportion [SE], 96.7% [1.0]), and White (weighted proportion [SE], 74.2% [3.7]). Approximately 6.6% of patients met criteria for past-year CUD. The SIS-C had an area under receiver operating characteristic curve of 0.89 (95% CI, 0.78-0.96) for identifying CUD. A threshold of less than monthly cannabis use balanced sensitivity (0.88) and specificity (0.83) for detecting CUD. In populations with a 6% prevalence of CUD, predictive values of a positive screen ranged from 17% to 34%, while predictive values of a negative screen ranged from 97% to 100%.

Conclusions: In this diagnostic study, the SIS-C had excellent performance characteristics in routine care as a screen for CUD. While high negative predictive values suggest that the SIS-C accurately identifies patients without CUD, low positive predictive values indicate a need for further diagnostic assessment following positive results when screening for CUD in primary care.

Related protocols: CTN-0077-Ot

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

This pilot study (related to CTN-0065) evaluated whether use of evidence-based implementation strategies to integrate care for cannabis and other drug use into primary care (PC) as part of Behavioral Health Integration (BHI) increased diagnosis and treatment of substance use disorders (SUDs).

Patients who visited the three pilot PC sites were eligible. Implementation strategies included practice coaching, electronic health record decision support, and performance feedback (3/2015-4/2016). BHI introduced annual screening for past-year cannabis and other drug use, a Symptom Checklist for DSM-5 SUDs, and shared decision-making about treatment options. Main analyses tested whether the proportions of PC patients diagnosed with, and treated for, new cannabis or other drug use disorders (CUDs and DUDs, respectively), differed significantly pre- and post-implementation.

Of 39,599 eligible patients, 57% and 59% were screened for cannabis and other drug use, respectively. Among PC patients reporting daily cannabis use (2%) or any drug use (1%), 51% and 37%, respectively, completed an SUD Symptom Checklist. The proportion of PC patients with newly diagnosed CUD increased significantly post-implementation (5 v 17 per 10,000 patients, p < 0.0001), but not other DUDs (10 vs 13 per 10,000, p = 0.24). The proportion treated for newly diagnosed CUDs did not increase post-implementation (1 vs 1 per 10,000, p = 0.80), but did for those treated for newly diagnosed other DUDs (1 vs 3 per 10,000, p = 0.038).

Conclusions: This pilot implementation of BHI to increase routine screening and assessment for SUDs was associated with increased new CUD diagnoses and a small increase in treatment of new other DUDs.

Related protocols: CTN-0065

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

Cannabis is the third most commonly used drug in the USA, after alcohol and tobacco, and the prevalence of cannabis use and cannabis use disorders (CUD) has doubled in the last decade, due in part to increasingly legalized access. Individuals who use cannabis have increased risk of behavioral health conditions, including depression, anxiety, and tobacco, alcohol, and other substance use disorders, but little is known about the association between frequency of cannabis use and behavioral health conditions among primary care patients. This population-based study of primary care patients reports on the prevalence of common behavioral health conditions across cannabis use frequency.

Using electronic health record data collected as part of CTN-0065 in a large health system in Washington State, Kaiser Permanente Washington, cannabis frequency was categories into three levels of past-year use: none, less than daily, and daily. Other behavioral health conditions identified through screening included depression symptoms, unhealthy alcohol use, and any illicit drug and/or medication misuse. Also assessed in the year prior to the screen were EHR-documented tobacco use and composite indicators for both mental health and substance use disorder diagnoses.

Analysis revealed a strong association between the frequency of cannabis use and tobacco use, depression symptoms, and other drug use, as well as diagnosed mental health and substance use disorders. Tobacco and unhealthy alcohol use were most common among young adult patients who reported daily and any past-year cannabis use, respectively. Among patients who used cannabis daily, nearly 50% reported depression symptoms and more than 35% had a past-year mental health disorder diagnosis.

Conclusions: Asking about the frequency of cannabis use as part of routine behavioral health screening primary care, in a state with legalized use, identifies patients at increased risk for substance use and mental health conditions.

Related protocols: CTN-0065

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 is the Results Article for CTN-0065.

Over 12% of U.S. adults report past-year cannabis use, and among those who use daily, 25% or more have a cannabis use disorder. Use is increasing as legal access expands, yet cannabis use is not routinely assessed in primary care, and little is known about use among primary care patients and relevant demographic and behavioral health subgroups. This study, from NIDA Clinical Trials Network protocol CTN-0065 (Evaluation of Drug Screening Implementation in Primary Care), describes the prevalence and frequency of past-year cannabis use among primary care patients assessed for use during a primary care visit.

This observational cohort study included adults who made a visit to primary care clinics with annual behavioral health screening, including a single-item question about frequency past-year cannabis use (March 2015-February 2016; n=29,857). Depression, alcohol, and other drug use were also assessed by behavioral health screening. Screening results, tobacco use, and diagnoses for past-year behavioral health conditions (e.g. mental health and substance use disorders) were obtained from EHRs.

Among patients who completed the cannabis use question (n=22,095; 74% of eligible patients), 15.3% (14.8-15.8%) reported any past-year use: 12.2% (11.8-12.6%) less than daily, and 3.1% (2.9-3.3%) daily. Among 2228 patients age 18-29 years, 36% (34-38%) reported any cannabis use and 8.1% (7-9.3%) daily use. Daily cannabis use was common among men age 18-29 years who used tobacco or screened positive for depression: 25.5% (18.8-32.1%) and 31.7% (23.3-50%) respectively.

Conclusions: This study of the prevalence and frequency of cannabis use among primary care patients, in a state with legalized use, found that most primary care patients who completed recommended routine behavioral health screening (e.g., depression and alcohol) also completed a question about past-year cannabis use. In addition, while 15% of all primary care patients reported any past-year cannabis use, the prevalence was much higher in important patient subgroups. Most notably, more than 1 in 4 younger men who used tobacco or screened positive for depression reported high-risk daily cannabis use. Routinely asking about cannabis use could promote recognition of patients who may benefit from primary care discussions about their cannabis use.