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BackgroundMethamphetamine use disorder (MethUD) disproportionately affects men who have sex exclusively with men or with men and women (collectively MSM/W), compared to men who have sex with women (MSW). This study is the first MethUD medication trial to compare treatment effect for these groups, hypothesizing that extended-release injectable naltrexone 380mg every 3 weeks plus oral extended-release bupropion 450mg daily would be less effective for MSM/W than MSW.MethodsData come from men (N = 246) in a multi-site, double-blind, randomized, placebo-controlled trial with sequential parallel comparison design. In Stage 1 (6-weeks), participants were randomized to active treatment or placebo. In Stage 2 (6-weeks), Stage 1 placebo non-responders were rerandomized. Treatment response was ≥3 methamphetamine-negative urine samples, out of four obtained at the end of Stages 1 and 2. Treatment effect was the active-versus-placebo between-group difference in the weighted average Stages 1 and 2 responses.ResultsMSM/W (n = 151) were more likely than MSW (n = 95) to be Hispanic, college-educated, and living with HIV. Adjusting for demographics, among MSM/W, response rates were 13.95 % (active treatment) and 2.78 % (placebo) in Stage 1; 23.26 % (active treatment) and 4.26 % (placebo) in Stage 2. Among MSW, response rates were 7.69 % (active treatment) and 5.80 % (placebo) in Stage 1; 3.57 % (active treatment) and 0 % (placebo) in Stage 2. Treatment effect was significantly larger for MSM/W (h = 0.1479) than MSW (h = 0.0227) (p = 0.04).ConclusionsFindings suggest efficacy of extended-release naltrexone plus bupropion for MSM/W, a population heavily burdened by MethUD. While a secondary outcome, this intriguing finding merits testing in prospective trials.

BackgroundThe co-occurrence of suicidality and substance use disorders has been well established, but rating scales to examine suicidal behavior and risk are sparse among participants with substance use disorders. We examined the psychometric properties of the 16-item Concise Health Risk Tracking Scale - Self Report (CHRT-SR16) to measure suicidality among adults with moderate-to-severe methamphetamine use disorder.MethodsParticipants (n = 403) with moderate-to-severe methamphetamine use disorder completed the CHRT-SR16 as part of a randomized, double-blind, placebo-controlled pharmacotherapy trial. The CHRT-SR16 factor structure was assessed using confirmatory factor analysis (CFA). Internal consistency was estimated with coefficients alpha (α) and omega (ω), test-retest reliability with intraclass correlation coefficient (ICC) and standard error of measurement, and convergent validity using Spearman's ρ rank order correlation coefficient test between CHRT-SR16 factors and the Patient Health Questionnaire (PHQ-9). The analyses utilized baseline and week 1 data (for test-retest reliability only).ResultsCFA revealed a seven-factor model of Pessimism, Helplessness, Social Support, Despair, Impulsivity, Irritability, and Suicidal Thoughts as the best-fitting model. The CHRT-SR16 also exhibited strong internal consistency (α = 0.89; ω = 0.89), test-retest reliability (ICC = 0.78) and convergent validity with the PHQ-9 total score (ρ = 0.62).ConclusionThe CHRT-SR16 showed strong psychometric properties in a sample of participants with primary methamphetamine use disorder.Clinicaltrialsgov identifierNCT03078075.

BackgroundThe use of naltrexone plus bupropion to treat methamphetamine use disorder has not been well studied.MethodsWe conducted this multisite, double-blind, two-stage, placebo-controlled trial with the use of a sequential parallel comparison design to evaluate the efficacy and safety of extended-release injectable naltrexone (380 mg every 3 weeks) plus oral extended-release bupropion (450 mg per day) in adults with moderate or severe methamphetamine use disorder. In the first stage of the trial, participants were randomly assigned in a 0.26:0.74 ratio to receive naltrexone-bupropion or matching injectable and oral placebo for 6 weeks. Those in the placebo group who did not have a response in stage 1 underwent rerandomization in stage 2 and were assigned in a 1:1 ratio to receive naltrexone-bupropion or placebo for an additional 6 weeks. Urine samples were obtained from participants twice weekly. The primary outcome was a response, defined as at least three methamphetamine-negative urine samples out of four samples obtained at the end of stage 1 or stage 2, and the weighted average of the responses in the two stages is reported. The treatment effect was defined as the between-group difference in the overall weighted responses.ResultsA total of 403 participants were enrolled in stage 1, and 225 in stage 2. In the first stage, 18 of 109 participants (16.5%) in the naltrexone-bupropion group and 10 of 294 (3.4%) in the placebo group had a response. In the second stage, 13 of 114 (11.4%) in the naltrexone-bupropion group and 2 of 111 (1.8%) in the placebo group had a response. The weighted average response across the two stages was 13.6% with naltrexone-bupropion and 2.5% with placebo, for an overall treatment effect of 11.1 percentage points (Wald z-test statistic, 4.53; P

Background and aims: Extended‐release naltrexone (XR‐NTX) and sublingual buprenorphine (SL‐BUP) are both approved for opioid use disorder (OUD) treatment in any medical setting. We aimed to compare the real‐world effectiveness of XR‐NTX and SL‐BUP. Design and setting: This was an observational active comparator, new user cohort study of Medicaid claims records for patients in New Jersey and California, USA, 2016–19. Participants/cases: The participants were adult Medicaid patients aged 18–64 years who initiated XR‐NTX or SL‐BUP for maintenance treatment of OUD and did not use medications for OUD in the 90 days before initiation. Our cohort included 1755 XR‐NTX and 9886 SL‐BUP patients. Measurements: We examined two outcomes up to 180 days after medication initiation: (1) composite of medication discontinuation and death and (2) composite of overdose and death. Findings In adjusted analyses, treatment with XR‐NTX was more likely to result in discontinuation or death by the end of follow‐up than treatment with SL‐BUP: cumulative risk 75.9% [95% confidence interval (CI) = 73.9%, 77.9%] versus 62.2% (95% CI = 61.2%, 63.2%), respectively (risk difference = 13.7 percentage points, 95% CI = 11.4, 16.0). There was minimal difference in the cumulative risk of overdose or death by the end of follow‐up: XR‐NTX 3.9% (95% CI = 3.0%, 4.8%) versus SL‐BUP 3.3% (95% CI = 2.9%, 3.7%); risk difference = 0.5 percentage points, 95% CI = –0.4, 1.5. Results were consistent across sensitivity analyses. Conclusions: Medicaid patients in California and New Jersey, USA, receiving treatment for opioid use disorder stayed in treatment longer on sublingual buprenorphine than on extended‐release naltrexone, but the risk of overdose was similar. Most patients in this study discontinued medication within 6 months, regardless of which medication was initiated. [ABSTRACT FROM AUTHOR]

Objective: The opioid intervention court (OIC) is an innovative, preplea 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 ofMOUD, (iii) number of days toMOUD 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 nomore 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. [ABSTRACT FROM AUTHOR]

Objective: The authors examined the prevalence and correlates of co-occurring opioid use disorder and opioid overdose among individuals receiving psychiatric services. Methods: 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: 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: These findings underscore the importance of providing opioid use disorder screening and treatment for patients receiving psychiatric services. [ABSTRACT FROM AUTHOR]

Aim: This study: (1) estimated the effect of early discontinuation of medication for opioid use disorder (MOUD) on overdose probability and (2) measured the relationship between patient characteristics and early discontinuation probability for each MOUD type. Design, setting and participants: This was a retrospective cohort using electronic health record data from the US Veterans Healthcare Administration. Participants were veterans initiating MOUD with buprenorphine (BUP), methadone (MET) or extended‐release naltrexone (XR‐NTX) from fiscal years 2012–19. A total of 39 284 veterans met eligibility with 22 721 (57.8%) initiating BUP, 12 652 (32.2%) initiating MET and 3911 (10.0%) initiating XR‐NTX. Measurements: Measurements (1) determined whether the veteran experienced an overdose in the 365 days after MOUD initiation (primary) and (2) early discontinuation of MOUD, defined as discontinuation before 180 days (secondary). We assumed that unobserved patient characteristics would jointly influence the probability of discontinuation and overdose. and estimated the joint distribution with a bivariate probit model. Findings We found that 9.0% of BUP initiators who experienced an overdose above the predicted 3.9% had no veteran‐discontinued BUP early; findings for XR‐NTX were similar, with 12.2% of initiators overdosing above the predicted 4.5%, but this was statistically inconclusive. We found no relationship between early discontinuation and overdose for MET initiators, probably due to the high risk of both events. The patient characteristics included in our post‐estimation exploratory analysis of early discontinuation varied by MOUD type, with between 14 (XR‐NTX) and 25 (BUP) tested. The only characteristics with at least one level showing a statistically significant change in probability of early discontinuation for all three MOUD types were geography and prior‐year exposure to psychotherapy, although direction and magnitude varied. Conclusion: Early discontinuation of buprenorphine, and probably extended‐release naltrexone, appears to be associated with a greater probability of experiencing a fatal or non‐fatal overdose among US veterans receiving medication for opioid use disorder (MOUD); methadone does not show the same association. There is no consistent set of characteristics among early discontinuers by MOUD type. [ABSTRACT FROM AUTHOR]

ObjectivesOnce-monthly intramuscular extended-release naltrexone (XR-NTX) has demonstrated efficacy for the prevention of relapse in opioid dependence, providing an alternative to agonist or partial agonist maintenance (ie, methadone and buprenorphine). The question remains, for whom is this unique treatment most efficacious and can patient-treatment matching factors be identified?MethodsA moderator analysis was conducted on a previously reported 24-week, placebo-controlled, multisite, randomized controlled trial of XR-NTX (n = 126) versus placebo (n = 124) among recently detoxified opioid-dependent adults in Russia, which showed XR-NTX superior to placebo in proportion of opioid abstinent weeks. The moderator analysis examined a dichotomous indicator of good clinical response-achieving at least 90% of weeks abstinent over the 24-week trial. A series of logistic regression models were fit for this outcome as functions of treatment (XR-NTX vs placebo), each baseline moderator variable, and their interactions. The 25 baseline variables included demographics, clinical severity (Addiction Severity Index, SF-36, and Clinical Global Impression-Severity), functioning (EQ-5D), craving, and HIV serostatus (HIV+).ResultsMore XR-NTX patients achieved 90% abstinence (64/126, 51%) versus placebo (39/124, 31%; P = 0.002). There were no significant interactions between baseline variables and treatment. There was a significant main effect of Clinical Global Impression-Severity score (P = 0.02), such that higher severity score was associated with a lower rate of Good Clinical Response.ConclusionsThe absence of significant baseline by treatment interactions indicates that no patient-treatment matching variables could be identified. This suggests that XR-NTX was effective in promoting abstinence from opioids across a range of demographic and severity characteristics.

Digital therapeutics can overcome many of the barriers to translation of evidence-based treatment for substance use, mental health, and other behavioral health conditions. Delivered via nearly ubiquitous platforms such as the web, smartphone applications, text messaging, and videoconferencing, digital therapeutics can transcend the time and geographic boundaries of traditional clinical settings so that individuals can access care when and where they need it. There is strong empirical support for digital therapeutic approaches for behavioral health, yet implementation science with regard to scaling use of digital therapeutics for behavioral health is still in its early stages. In this paper, we summarize the proceedings of a day-long workshop, “Implementation Science and Digital Therapeutics,” sponsored and hosted by the Center for Technology and Behavioral Health at Dartmouth College. The Center for Technology and Behavioral Health is an interdisciplinary P30 Center of Excellence funded by the National Institute on Drug Abuse, with the mission of promoting state-of-the-technology and state-of-the-science for the development, evaluation, and sustainable implementation of digital therapeutic approaches for substance use and related conditions. Workshop presentations were grounded in current models of implementation science. Directions and opportunities for collaborative implementation science research to promote broad adoption of digital therapeutics for behavioral health are offered.

The concept of treatment-refractory addiction, proposed by Eric Strain in this edition of the Journal, has the potential to invigorate the field of addiction treatment and research by focusing on a phenomenon that is familiar to any clinician treating patientswith substance use disorders, namely, the patient who does not experience sufficient improvement from standard treatments. An analogy is drawn to the concept of treatment-resistant depression and the STAR*D study, which demonstrated an algorithmic approach to treatment, where if the first antidepressant medication tried did not result in remission from depression, subsequent trials of medications or cognitive behavioral therapy doubled the proportion of patients achieving remission. Recognizing treatment-refractory addiction challenges our field to develop analogous, stepwise, algorithmic approaches to treatment of substance use disorders, moving away from siloed treatment programs toward integrated treatment systems where alternative treatments are available, offering the kind of personalized, tailored forms of care used in the treatment of most other chronic illnesses. Like in STAR*D, research could focus on samples of patients who have not benefitted from initial trials of standard addiction treatments, addressing the key clinical question of what to do next when previous treatments fail. [ABSTRACT FROM AUTHOR]

The health care field has integrated advances into digital technology at an accelerating pace to improve health behavior, health care delivery, and cost-effectiveness of care. The realm of behavioral science has embraced this evolution of digital health, allowing for an exciting roadmap for advancing care by addressing the many challenges to the field via technological innovations. Digital therapeutics offer the potential to extend the reach of effective interventions at reduced cost and patient burden and to increase the potency of existing interventions. Intervention models have included the use of digital tools as supplements to standard care models, as tools that can replace a portion of treatment as usual, or as stand-alone tools accessed outside of care settings or direct to the consumer. To advance the potential public health impact of this promising line of research, multiple areas warrant further development and investigation. The Center for Technology and Behavioral Health (CTBH), a P30 Center of Excellence supported by the National Institute on Drug Abuse at the National Institutes of Health, is an interdisciplinary research center at Dartmouth College focused on the goal of harnessing existing and emerging technologies to effectively develop and deliver evidence-based interventions for substance use and co-occurring disorders. The CTBH launched a series of workshops to encourage and expand multidisciplinary collaborations among Dartmouth scientists and international CTBH affiliates engaged in research related to digital technology and behavioral health (eg, addiction science, behavioral health intervention, technology development, computer science and engineering, digital security, health economics, and implementation science). This paper summarizes a workshop conducted on the Development and Evaluation of Digital Therapeutics for Behavior Change, which addressed (1) principles of behavior change, (2) methods of identifying and testing the underlying mechanisms of behavior change, (3) conceptual frameworks for optimizing applications for mental health and addictive behavior, and (4) the diversity of experimental methods and designs that are essential to the successful development and testing of digital therapeutics. Examples were presented of ongoing CTBH projects focused on identifying and improving the measurement of health behavior change mechanisms and the development and evaluation of digital therapeutics. In summary, the workshop showcased the myriad research targets that will be instrumental in promoting and accelerating progress in the field of digital health and health behavior change and illustrated how the CTBH provides a model of multidisciplinary leadership and collaboration that can facilitate innovative, science-based efforts to address the health behavior challenges afflicting our communities.

Key Points: Question: For individuals undergoing medication treatment for opioid use disorder, can those who will return to opioid use be predicted at the individual level? Findings: In this decision analytical model using a harmonized data set of 2199 adults with opioid use disorder, incorporating treatment entry characteristics and urine drug screen results in the first 3 weeks of treatment improved model performance in predicting return to use. Meaning: These findings suggest that clinicians can use a web-based predictive model to stratify return-to-use risk when delivering care for patients with opioid use disorder. This decision analytical model uses a harmonized data set to develop an individual-level prediction tool to assess the risk of return to use in patients treated for opioid use disorder. Importance: No existing model allows clinicians to predict whether patients might return to opioid use in the early stages of treatment for opioid use disorder. Objective: To develop an individual-level prediction tool for risk of return to use in opioid use disorder. Design, Setting, and Participants: This decision analytical model used predictive modeling with individual-level data harmonized in June 1, 2019, to October 1, 2022, from 3 multicenter, pragmatic, randomized clinical trials of at least 12 weeks' duration within the National Institute on Drug Abuse Clinical Trials Network (CTN) performed between 2006 and 2016. The clinical trials covered a variety of treatment settings, including federally licensed treatment sites, physician practices, and inpatient treatment facilities. All 3 trials enrolled adult participants older than 18 years, with broad pragmatic inclusion and few exclusion criteria except for major medical and unstable psychiatric comorbidities. Intervention: All participants received 1 of 3 medications for opioid use disorder: methadone, buprenorphine, or extended-release naltrexone. Main Outcomes and Measures: Predictive models were developed for return to use, which was defined as 4 consecutive weeks of urine drug screen (UDS) results either missing or positive for nonprescribed opioids by week 12 of treatment. Results: The overall sample included 2199 trial participants (mean [SD] age, 35.3 [10.7] years; 728 women [33.1%] and 1471 men [66.9%]). The final model based on 4 predictors at treatment entry (heroin use days, morphine- and cocaine-positive UDS results, and heroin injection in the past 30 days) yielded an area under the receiver operating characteristic curve (AUROC) of 0.67 (95% CI, 0.62-0.71). Adding UDS in the first 3 treatment weeks improved model performance (AUROC, 0.82; 95% CI, 0.78-0.85). A simplified score (CTN-0094 OUD Return-to-Use Risk Score) provided good clinical risk stratification wherein patients with weekly opioid-negative UDS results in the 3 weeks after treatment initiation had a 13% risk of return to use compared with 85% for those with 3 weeks of opioid-positive or missing UDS results (AUROC, 0.80; 95% CI, 0.76-0.84). Conclusions and Relevance: The prediction model described in this study may be a universal risk measure for return to opioid use by treatment week 3. Interventions to prevent return to regular use should focus on this critical early treatment period. [ABSTRACT FROM AUTHOR]