Faculty Bibliography

OBJECTIVES/OBJECTIVE:Opioid use disorder (OUD) is a global concern. Urine drug screening uses opioid immunoassays to monitor OUD treatment response but is limited to yes/no results. Analytical cutoff variation complicates interstudy comparisons. This study investigated whether quantitative urinalysis can provide additional clinically meaningful treatment efficacy information and assessed the impact of different cutoffs on treatment differences. METHODS:Quantitative urine drug test data were analyzed from a randomized, active-controlled, parallel-group, double-blind, 31-week phase 3 trial (N = 428; December 29, 2015, to October 19, 2016) assessing CAM2038 subcutaneous (SC) buprenorphine (BPN) extended-release injections compared to daily sublingual (SL) BPN/naloxone (BPN/NX) tablets, and equivalent placebos, in OUD treatment (NCT02651584). Urine samples were analyzed by gas or liquid chromatography with mass spectrometry. The European Medicines Agency (EMA)-directed primary endpoint, based on opioid detection above the lower limit of quantification (LLOQ), was explored using different cutoffs. RESULTS:Using the LLOQ, the mean percentage of opioid-negative samples was 35.1% and 28.4% for CAM2038 and SL BPN/NX, respectively (mean difference [95% confidence interval], 6.7% [-0.1% to 13.6%]). Using standard cutoffs (1 ng/mg creatinine [fentanyl/norfentanyl], 300 ng/mg creatinine [other opioids]), results were 41.2% and 32.2% (9.0% [1.8%-16.1%]). Increasing cutoffs led to greater differences favoring CAM2038. Significant differences in mean concentrations over time and cumulative distribution of exposure to different opioids also favored CAM2038. The difference in fentanyl exposure between treatments was nonsignificant. CONCLUSIONS:Quantitative urinalysis provides insights into opioid use beyond assessment of abstinence. Study outcomes are impacted by analytical thresholds, which should be carefully considered when designing, interpreting, and comparing clinical trial results.

BACKGROUND: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. METHODS: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. RESULTS: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.

BACKGROUND:Evidence-based practices for reducing opioid-related overdose deaths include overdose education and naloxone distribution, the use of medications for the treatment of opioid use disorder, and prescription opioid safety. Data are needed on the effectiveness of a community-engaged intervention to reduce opioid-related overdose deaths through enhanced uptake of these practices. METHODS:In this community-level, cluster-randomized trial, we randomly assigned 67 communities in Kentucky, Massachusetts, New York, and Ohio to receive the intervention (34 communities) or a wait-list control (33 communities), stratified according to state. The trial was conducted within the context of both the coronavirus disease 2019 (Covid-19) pandemic and a national surge in the number of fentanyl-related overdose deaths. The trial groups were balanced within states according to urban or rural classification, previous overdose rate, and community population. The primary outcome was the number of opioid-related overdose deaths among community adults. RESULTS:During the comparison period from July 2021 through June 2022, the population-averaged rates of opioid-related overdose deaths were similar in the intervention group and the control group (47.2 deaths per 100,000 population vs. 51.7 per 100,000 population), for an adjusted rate ratio of 0.91 (95% confidence interval, 0.76 to 1.09; P = 0.30). The effect of the intervention on the rate of opioid-related overdose deaths did not differ appreciably according to state, urban or rural category, age, sex, or race or ethnic group. Intervention communities implemented 615 evidence-based practice strategies from the 806 strategies selected by communities (254 involving overdose education and naloxone distribution, 256 involving the use of medications for opioid use disorder, and 105 involving prescription opioid safety). Of these evidence-based practice strategies, only 235 (38%) had been initiated by the start of the comparison year. CONCLUSIONS:In this 12-month multimodal intervention trial involving community coalitions in the deployment of evidence-based practices to reduce opioid overdose deaths, death rates were similar in the intervention group and the control group in the context of the Covid-19 pandemic and the fentanyl-related overdose epidemic. (Funded by the National Institutes of Health; HCS ClinicalTrials.gov number, NCT04111939.).

Contingency Management (CM) is a psychological treatment that aims to change behavior with financial incentives. In substance use disorders (SUDs), deployment of CM has been enriched by longstanding discussions around the cost-effectiveness of prized-based and voucher-based approaches. In prize-based CM, participants earn draws to win prizes, including small incentives to reduce costs, and the number of draws escalates depending on the duration of maintenance of abstinence. In voucher-based CM, participants receive a predetermined voucher amount based on specific substance test results. While both types have enhanced treatment outcomes, there is room for improvement in their cost-effectiveness: the voucher-based system requires enduring financial investment; the prize-based system might sacrifice efficacy. Previous work in computational psychiatry of SUDs typically employs frameworks wherein participants make decisions to maximize their expected compensation. In contrast, we developed new frameworks that clinical decision-makers choose actions, CM structures, to reinforce the substance abstinence behavior of participants. We consider the choice of the voucher or prize to be a sequential decision, where there are two pivotal parameters: the prize probability for each draw and the escalation rule determining the number of draws. Recent advancements in Reinforcement Learning, more specifically, in off-policy evaluation, afforded techniques to estimate outcomes for different CM decision scenarios from observed clinical trial data. We searched CM schemas that maximized treatment outcomes with budget constraints. Using this framework, we analyzed data from the Clinical Trials Network to construct unbiased estimators on the effects of new CM schemas. Our results indicated that the optimal CM schema would be to strengthen reinforcement rapidly in the middle of the treatment course. Our estimated optimal CM policy improved treatment outcomes by 32% while maintaining costs. Our methods and results have broad applications in future clinical trial planning and translational investigations on the neurobiological basis of SUDs.

OBJECTIVE/UNASSIGNED:The authors examined the prevalence and correlates of co-occurring opioid use disorder and opioid overdose among individuals receiving psychiatric services. METHODS/UNASSIGNED:This was a cross-sectional study of adults with continuous enrollment in New York State Medicaid who received at least one psychiatric service in 2020 (N=523,885). Logistic regression models were used to examine the correlates of both opioid use disorder and overdose. RESULTS/UNASSIGNED:In the study sample, the prevalence rate of opioid use disorder was 8.1%; within this group, 7.7% experienced an opioid overdose in the study year. Opioid use disorder rates were lower among younger (18-24 years; 2.0%) and older (≥65 years; 3.1%) adults and higher among men (11.1%) and among those residing in rural areas (9.9%). Compared with Whites (9.4%), opioid use disorder rates were lower for Asian Americans (2.0%, adjusted odds ratio [AOR]=0.22) and Blacks (6.8%, AOR=0.76) and higher for American Indians (13.2%, AOR=1.43) and Hispanics (9.6%, AOR=1.29). Individuals with any substance use (24.9%, AOR=5.20), posttraumatic stress (15.7%, AOR=2.34), bipolar (14.9%, AOR=2.29), or anxiety (11.3%, AOR=2.18) disorders were more likely to have co-occurring opioid use disorder; those with conduct (4.5%, AOR=0.51), adjustment (7.4%, AOR=0.88), or schizophrenia spectrum (7.4%, AOR=0.87) disorders were less likely to have opioid use disorder. Those with suicidality (23.9%, AOR=3.83) or economic instability (23.7%, AOR=3.35) had higher odds of having opioid use disorder. Overdose odds were higher among individuals with suicidality (34.0%, AOR=6.82) and economic instability (16.0%, AOR=2.57). CONCLUSIONS/UNASSIGNED:These findings underscore the importance of providing opioid use disorder screening and treatment for patients receiving psychiatric services.

IMPORTANCE:Fentanyl has exacerbated the opioid use disorder (OUD) and opioid overdose epidemic. Data on the effectiveness of medications for OUD among patients using fentanyl are limited. OBJECTIVE:To assess the effectiveness of sublingual or extended-release injection formulations of buprenorphine for the treatment of OUD among patients with and without fentanyl use. DESIGN, SETTING, AND PARTICIPANTS:Post hoc analysis of a 24-week, randomized, double-blind clinical trial conducted at 35 outpatient sites in the US from December 2015 to November 2016 of sublingual buprenorphine-naloxone vs extended-release subcutaneous injection buprenorphine (CAM2038) for patients with OUD subgrouped by presence vs absence of fentanyl or norfentanyl in urine at baseline. Study visits with urine testing occurred weekly for 12 weeks, then 6 times between weeks 13 and 24. Data were analyzed on an intention-to-treat basis from March 2022 to August 2023. INTERVENTION:Weekly and monthly subcutaneous buprenorphine vs daily sublingual buprenorphine-naloxone. MAIN OUTCOMES AND MEASURES:Retention in treatment, percentage of urine samples negative for any opioids (missing values imputed as positive), percentage of urine samples negative for fentanyl or norfentanyl (missing values not imputed), and scores on opiate withdrawal scales and visual analog craving scales. RESULTS:Of 428 participants, 123 (subcutaneous buprenorphine, n = 64; sublingual buprenorphine-naloxone, n = 59; mean [SD] age, 39.1 [10.8] years; 75 men [61.0%]) had evidence of baseline fentanyl use and 305 (subcutaneous buprenorphine, n = 149; buprenorphine-naloxone, n = 156; mean [SD] age, 38.1 [11.1] years; 188 men [61.6%]) did not have evidence of baseline fentanyl use. Study completion was similar between the fentanyl-positive (60.2% [74 of 123]) and fentanyl-negative (56.7% [173 of 305]) subgroups. The mean percentage of urine samples negative for any opioid were 28.5% among those receiving subcutaneous buprenorphine and 18.8% among those receiving buprenorphine-naloxone in the fentanyl-positive subgroup (difference, 9.6%; 95% CI, -3.0% to 22.3%) and 36.7% among those receiving subcutaneous buprenorphine and 30.6% among those receiving buprenorphine-naloxone in the fentanyl-negative subgroup (difference, 6.1%; 95% CI, -1.9% to 14.1%), with significant main associations of baseline fentanyl status and treatment group. In the fentanyl-positive subgroup, the mean percentage of urine samples negative for fentanyl during the study was 74.6% among those receiving subcutaneous buprenorphine vs 61.9% among those receiving sublingual buprenorphine-naloxone (difference, 12.7%; 95% CI, 9.6%-15.9%). Opioid withdrawal and craving scores decreased rapidly after treatment initiation across all groups. CONCLUSIONS AND RELEVANCE:In this post hoc analysis of a randomized clinical trial of sublingual vs extended-release injection buprenorphine for OUD, buprenorphine appeared to be effective among patients with baseline fentanyl use. Patients with fentanyl use had fewer opioid-negative urine samples during the trial compared with the fentanyl-negative subgroup. These findings suggest that the subcutaneous buprenorphine formulation may be more effective at reducing fentanyl use. TRIAL REGISTRATION:ClinicalTrials.gov Identifier: NCT02651584.

IMPORTANCE/UNASSIGNED:The HEALing Communities Study (HCS) evaluated the effectiveness of the Communities That HEAL (CTH) intervention in preventing fatal overdoses amidst the US opioid epidemic. OBJECTIVE/UNASSIGNED:To evaluate the impact of the CTH intervention on total drug overdose deaths and overdose deaths involving combinations of opioids with psychostimulants or benzodiazepines. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This randomized clinical trial was a parallel-arm, multisite, community-randomized, open, and waitlisted controlled comparison trial of communities in 4 US states between 2020 and 2023. Eligible communities were those reporting high opioid overdose fatality rates in Kentucky, Massachusetts, New York, and Ohio. Covariate constrained randomization stratified by state allocated communities to the intervention or control group. Trial groups were balanced by urban or rural classification, 2016-2017 fatal opioid overdose rate, and community population. Data analysis was completed by December 2023. INTERVENTION/UNASSIGNED:Increased overdose education and naloxone distribution, treatment with medications for opioid use disorder, safer opioid prescribing practices, and communication campaigns to mitigate stigma and drive demand for evidence-based interventions. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was the number of drug overdose deaths among adults (aged 18 years or older), with secondary outcomes of overdose deaths involving specific opioid-involved drug combinations from death certificates. Rates of overdose deaths per 100 000 adult community residents in intervention and control communities from July 2021 to June 2022 were compared with analyses performed in 2023. RESULTS/UNASSIGNED:In 67 participating communities (34 in the intervention group, 33 in the control group) and including 8 211 506 participants (4 251 903 female [51.8%]; 1 273 394 Black [15.5%], 603 983 Hispanic [7.4%], 5 979 602 White [72.8%], 354 527 other [4.3%]), the average rate of overdose deaths involving all substances was 57.6 per 100 000 population in the intervention group and 61.2 per 100 000 population in the control group. This was not a statistically significant difference (adjusted rate ratio [aRR], 0.92; 95% CI, 0.78-1.07; P = .26). There was a statistically significant 37% reduction (aRR, 0.63; 95% CI, 0.44-0.91; P = .02) in death rates involving an opioid and psychostimulants (other than cocaine), and nonsignificant reductions in overdose deaths for an opioid with cocaine (6%) and an opioid with benzodiazepine (1%). CONCLUSION AND RELEVANCE/UNASSIGNED:In this clinical trial of the CTH intervention, death rates involving an opioid and noncocaine psychostimulant were reduced; total deaths did not differ statistically. Community-focused data-driven interventions that scale up evidence-based practices with communications campaigns may effectively reduce some opioid-involved polysubstance overdose deaths. TRIAL REGISTRATION/UNASSIGNED:ClinicalTrials.gov Identifier: NCT04111939.

OBJECTIVE:The opioid intervention court (OIC) is an innovative, pre-plea treatment court to facilitate rapid linkage to medications for opioid use disorder (MOUD) for people at risk of overdose. This study compares participants in OIC and participants with opioid use problems in a traditional drug treatment court model on (i) initiation for any substance use (SU) treatment, (ii) initiation of MOUD, (iii) number of days to MOUD initiation, and (iv) retention in the OIC program/retention on MOUD. METHODS:We used administrative court records from n = 389 OIC and n = 229 drug court participants in 2 counties in New York State. Differences in outcomes by court were assessed using logistic, multinomial, or linear regressions. RESULTS:After adjusting for current charge severity, gender, race/ethnicity, age, and county, OIC participants were no more likely to initiate any SU treatment but were significantly more likely to initiate MOUD (81.2% OIC vs 45.9% drug court, P < 0.001) and were more quickly linked to any SU treatment (hazard ratio = 1.68, 95% confidence interval = 1.35-2.08) and MOUD (hazard ratio = 4.25, 95% confidence interval = 3.23-5.58) after starting the court. Retention in court/MOUD was higher among drug court participants and may speak to the immediate sanctions (eg, jail) for noncompliance with drug court directives as compared with opioid court, which does not carry such immediate sanctions for noncompliance. CONCLUSIONS:These analyses suggest that the new OIC model can more rapidly link participants to treatment, including MOUD, as compared with traditional drug court model, and may demonstrate improved ability to immediately stabilize and reduce overdose risk in court participants.

BACKGROUND:The U.S. opioid overdose crisis persists. Outpatient behavioral health services (BHS) are essential components of a comprehensive response to opioid use disorder and overdose fatalities. The Helping to End Addiction Long-Term® (HEALing) Communities Study developed the Communities That HEAL (CTH) intervention to reduce opioid overdose deaths in 67 communities in Kentucky, Ohio, New York, and Massachusetts through the implementation of evidence-based practices (EBPs), including BHS. This paper compares the rate of individuals receiving outpatient BHS in Wave 1 intervention communities (n = 34) to waitlisted Wave 2 communities (n = 33). METHODS:Medicaid data included individuals ≥18 years of age receiving any of five BHS categories: intensive outpatient, outpatient, case management, peer support, and case management or peer support. Negative binomial regression models estimated the rate of receiving each BHS for Wave 1 and Wave 2. Effect modification analyses evaluated changes in the effect of the CTH intervention between Wave 1 and Wave 2 by research site, rurality, age, sex, and race/ethnicity. RESULTS:No significant differences were detected between intervention and waitlisted communities in the rate of individuals receiving any of the five BHS categories. None of the interaction effects used to test the effect modification were significant. CONCLUSIONS:Several factors should be considered when interpreting results-no significant intervention effects were observed through Medicaid claims data, the best available data source but limited in terms of capturing individuals reached by the intervention. Also, the 12-month evaluation window may have been too brief to see improved outcomes considering the time required to stand-up BHS. TRIAL REGISTRATION/BACKGROUND:Clinical Trials.gov http://www. CLINICALTRIALS/RESULTS:gov: Identifier: NCT04111939.

BACKGROUND:Extended-release naltrexone (NTX) is an opioid antagonist approved for relapse prevention after medical withdrawal. Its therapeutic effect is dependent on the NTX plasma level, and as it decreases, patients may lack protection against relapse and overdose. Therefore, identifying the minimally effective NTX level needed to block opioid-induced subjective effects has important clinical implications. METHODS:This secondary, individual-level analysis of data collected in a human laboratory study was conducted to evaluate the relationship between NTX levels and subjective effects of an intravenously administered 25-mg challenge dose of heroin in non-treatment-seeking participants with opioid use disorder (N = 12). Subjective ratings of drug liking using a 100-mm visual analog scale (VAS) and NTX levels were measured across 6 weeks after participants received a single injection of either extended-release NTX 192 mg (N = 6) or 384 mg (N = 6). Cubic spline mixed-effects models were used to provide 95% prediction intervals for individual changes in liking scores as a function of NTX levels. RESULTS:Naltrexone levels above 2 ng/mL blocked nearly all VAS ratings of drug liking after intravenous heroin administration. Participants with NTX levels ≥ 2 ng/mL had minimal (≤20 mm) changes from placebo in VAS ratings of drug liking based on 95% prediction intervals. In contrast, NTX levels < 2 ng/mL were associated with greater variability in individual-level subjective responses. CONCLUSIONS:In clinical practice, a plasma level range of 1 to 2 ng/mL is considered to be therapeutic in providing heroin blockade. The current findings suggest that a higher level (>2 ng/mL) may be needed to produce a consistent blockade.