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Abstract: Background and aim: Extended-release injectable naltrexone (XR-Naltrexone) is an effective treatment for opioid use disorder (OUD); however, initiation can be challenging as it requires an opioid-free period. This exploratory analysis examines patient characteristics associated with successful initiation of XR-Naltrexone in the National Drug Abuse Treatment Clinical Trials Network (CTN-0051) Extended-Release Naltrexone versus Buprenorphine for Opioid Treatment (X:BOT) trial. Methods: Patient demographics and clinical variables associated with successful XR-Naltrexone initiation were examined among 283 participants with OUD randomized to XR-Naltrexone in the X:BOT trial. Variables included severity of opioid use, characteristics of opioid and other substance use, treatment history, psychiatric history, baseline depression, and pain. Logistic regression models were used to estimate the effect of variables on the odds of induction success. Results: 204 (72%) of 283 participants randomized to receive XR-Naltrexone completed successful induction. Housing status and pain were significantly associated with XR-Naltrexone induction status. Reported homelessness was significantly associated with higher odds of successful XR-Naltrexone induction (OR: 2.31; 95% CI: 1.12, 4.76). Individuals that reported moderate or extreme pain on the EuroQoL had half the odds of successful induction compared to those without pain (OR: 0.49; 95% CI: 0.27, 0.89). Conclusions: Among patients with OUD initiating treatment on inpatient units, homelessness was associated with greater likelihood of successfully initiating XR-Naltrexone, while chronic pain was associated with lower likelihood of XR-Naltrexone initiation. Future research on XR-Naltrexone initiation should consider tailoring treatment based on housing status and other social determinants, and evaluation and management of pain. Related protocols: CTN-0051

Abstract:

Background & Objectives: Depression and suicidal ideation are prevalent in patients with opioid use disorder (OUD). This study examined changes in suicidal ideation during OUD treatment with buprenorphine-naloxone or extended-release naltrexone using data from CTN-0051.

Methods: 570 adults with OUD (29.6% female) were recruited into a National Drug Abuse Clinical Trials Network randomized trial (CTN-0051) comparing extended-release naltrexone versus buprenorphine-naloxone for opioid relapse prevention (X:BOT). Suicidal ideation was assessed at baseline and regular intervals over 24 weeks using continuous self-reported and binary clinician-rated measures from the Concise Health Risk Tracking-Self Report and the Hamilton Depression Rating Scale, respectively. A mixed-effects model was used to assess the association between continuous outcome self-reported suicidal ideation and treatment over time while adjusted for baseline suicidal ideation.

Results: Continuous self-report suicidal ideation scores decreased in both groups with a significant time-by-treatment interaction indicating that the treatment effect differed over time (F(11, 3497) = 1.81, p = .0464). Scores were significantly lower in the buprenorphine group only in weeks 1 and 3 and when averaged across weeks 1-4. Binary clinician-rated suicidal ideation dropped from 15 (5.25%) and 12 (4.24%) at baseline, to 5 (1.89%) and 3 (1.49%) at week 1, for buprenorphine and naltrexone groups, respectively.

Conclusions: OUD treatment with extended-release naltrexone or buprenorphine-naloxone was associated with suicidal ideation reductions from the first week. Suicidal ideation was lower with buprenorphine-naloxone in the first 4 weeks, with no significant differences thereafter. Despite overall low suicidal ideation scores and modest differences, these findings suggest beneficial effects of both treatments in individuals with OUD and mild baseline suicidality.

Related protocols: CTN-0051

Abstract:

Aims: Cannabis use is highly prevalent in patients seeking treatment for opioid use disorder. Studies have shown mixed results on the association between cannabis use and opioid use as well as the impact of MOUD on cannabis use. The current study aims to investigate the effects of buprenorphine versus naltrexone on cannabis use outcomes in treatment seeking individuals with Opioid Use Disorder (OUD).

Methods: The current study was based on data from the CTN-0051 X:BOT trial, which compared the opioid relapse-free survival outcomes of two treatment seeking groups, one receiving Extended-Release Naltrexone (XR-naltrexone) (N=283) versus another receiving Buprenorphine-Naloxone (N=287) for OUD. A mixed-effects logistic regression model including treatment assignment (buprenorphine-naloxone vs XR-naltrexone), time, and a time by treatment interaction was run on the sample with the odds of cannabis use as the outcome, as well as two cross-lagged mediation models to explore the prospective mediation of cannabis use on opioid use outcomes (and opioid use on cannabis use outcomes) by treatment assignment during the trial.

Results: There was a significant effect of buprenorphine treatment on reduced cannabis use. Participants receiving buprenorphine treatment were 39% less likely to use cannabis than those receiving naltrexone over all the timepoints (p=.0499). No significant mediation was found between treatment assignment and opioid use on cannabis use outcomes or between treatment assignment and cannabis use on opioid use outcomes in this trial.

Conclusion: Participants in this trial receiving buprenorphine treatment for OUD used less cannabis than those receiving naltrexone treatment.

Related protocols: CTN-0051

Abstract:

Opioid use disorder (OUD) represents a significant public health challenge. Identifying variations in the severity of opioid withdrawal that can predict treatment success and may help improve the process of aligning patients with appropriate therapies could help improve outcomes. This study was a secondary latent class growth analysis (LCGA) of data from a randomized controlled trial that involved individuals seeking treatment for OUD (CTN-0051). Participants were 474 adults (270 taking buprenorphine, 204 on extended-release naltrexone (XR-NTX)) in a 24-week trial for OUD. Withdrawal was measured weekly using the Subjective Opioid Withdrawal Scale. Analysis found that a two-class model (high sustained withdrawal and low withdrawal classes) was most parsimonious among patients in both treatment arms. The experience of withdrawal was more intense in the high withdrawal class of the BUP arm when compared to the XTR arm (average M=22.9 vs. M=12.4 respectively). No differences were evident regarding age, sex, race, or ethnicity. There were significant differences in history of anxiety and history of depression.

Related protocols: CTN-0051

Abstract:

Several large-scale, pragmatic clinical trials on opioid use disorder (OUD) have been completed in the National Drug Abuse Treatment Clinical Trials Network (CTN). However, the resulting data have not been harmonized between the studies to compare the patient characteristics. This paper provides lessons learned from a large-scale harmonization process that are critical for all biomedical researchers collecting new data and those tasked with combining datasets.

Researchers harmonized data from multiple domains from CTN-0027 (N = 1269), which compared methadone and buprenorphine at federally licensed methadone treatment programs; CTN-0030 (N = 653), which recruited patients who used predominantly prescription opioids and were treated with buprenorphine; and CTN-0051 (N = 570), which compared buprenorphine and extended-release naltrexone (XR-NTX) and recruited from inpatient treatment facilities. Patient-level data were harmonized and a total of 23 database tables, with meticulous documentation, covering more than 110 variables, along with three tables with “meta-data” about the study design and treatment arms, were created. Domains included: social and demographic characteristics, medical and psychiatric history, self-reported drug use details and urine drug screening results, withdrawal, and treatment drug details.

In this paper, the authors summarize the numerous issues with the organization and fidelity of the publicly available data which were noted and resolved, and present results on patient characteristics across the three trials and the harmonized domains, respectively. A systematic harmonization of OUD clinical trial data can be accomplished, despite heterogeneous data coding and classification procedures, by standardizing commonly assessed characteristics. Similar methods, embracing database normalization and/or “tidy” data, should be used for future datasets in other substance use disorder clinical trials.

Related protocols: CTN-0027, CTN-0030, CTN-0051

Abstract:

Polysubstance use may complicate treatment outcomes for individuals who use opioids. This research aimed to examine the prevalence of polysubstance use in an opioid use disorder treatment trial population and polysubstance use’s association with opioid relapse and craving.

This study is a secondary data analysis of individuals with opioid use disorder who received at least one dose of medication (n=474) as part of a 24-week, multi-site, open label, randomized Clinical Trials Network study (CTN-0051, X:BOT) comparing the effectiveness of extended-release naltrexone versus buprenorphine. Models examined pretreatment polysubstance use and polysubstance use during the initial 4 weeks of treatment on outcomes of relapse by week 24 of the treatment trial and opioid craving.

Polysubstance use was generally not associated with treatment outcomes of opioid relapse and craving. Proportion of days of pretreatment sedative use was associated with increased likelihood of opioid relapse (OR: 1.01, 95% CI: 1.00–1.02). Proportion of days of cocaine use during the initial 4 weeks of treatment was associated with increased likelihood of opioid relapse (OR: 1.05, 95% CI: 1.01–1.09) but this effect was no longer significant once the potential of confounding by opioid use was considered. Sedative use during initial 4 weeks of treatment was associated with increased opioid craving (b: 0.77, 95% CI: 0.01–1.52). The study found no other significant relationships.

Conclusions: In the current study population, polysubstance use was only marginally associated with 24-week treatment outcomes.

Related protocols: CTN-0051

Abstract:

Racial and ethnic disparities in access to treatment and quality of treatment for opioid use disorder (OUD) have been identified in usual care settings. In contrast, disparities in treatment quality within clinical trials are relatively unexamined. This study aimed to estimate racial and ethnic differences in the dose of opioid agonist treatment for OUD in the first 4 weeks of treatment in clinical trials.

This cohort study performed analysis of the methadone and buprenorphine treatment arms of 3 trials conducted by the National Institute on Drug Abuse Clinical Trials Network between May 2006, and January 31, 2017, at multiple Clinical Trials Network sites across the US (CTN-0027, START, CTN-0030, POATS, and CTN-0051, X:BOT). Trial participants who were randomized to and initiated buprenorphine or methadone treatment and who identified as Hispanic, non-Hispanic Black, or non-Hispanic White were included in the present study. Data were analyzed from November 1, 2023, to August 5, 2024. THe main outcomes and measures were the maximum daily dose of buprenorphine or methadone received in each week for the first 4 weeks of treatment. The mean dose and percentage of patients receiving a higher dose (buprenorphine =16 mg and methadone =60 mg) were also compared across race and ethnicity groups.

A total of 1748 patients (1263 who initiated buprenorphine and 485 who initiated methadone treatment) were included in the analysis (1168 [66.8%] male; median age, 33 [IQR, 26-45] years). Of these, 138 patients (7.9%) identified as Black, 273 (15.6%) as Hispanic, and 1337 (76.5%) as White. In week 4, Black patients received buprenorphine doses 2.5 (95% CI -4.6 to -0.5) mg lower and methadone doses 16.7 (95% CI, -30.7 to -2.7) mg lower compared with White patients, after standardizing by age and sex. In week 4, the percentage of patients receiving a higher dose of medication (buprenorphine =16 mg; methadone =60 mg) was 16.9 (95% CI, -31.9 to -1.9) points lower for Black patients compared with White patients. Hispanic and White patients received similar buprenorphine doses; Hispanic patients received lower methadone doses than White patients.

Conclusions: In this cohort study of data from 3 clinical trials, White patients generally received higher doses of medication than Black patients. Future research is needed to understand the mechanisms of and interventions to reduce disparities in OUD treatment quality and how such disparities impact generalizability of trial results.

Note: An invited commentary piece on this article was also published by JAMA Network Open (Schiff DM, Nidey N, Tiako MJN. Dosing inequities in opioid use disorder treatment trials. JAMA Network Open 2024;7(10):e2436582.)

Related protocols: CTN-0027, CTN-0030, CTN-0051

Abstract:

A trial comparing extended-release naltrexone and sublingual buprenorphine-naloxone demonstrated higher relapse rates in individuals randomized to extended-release naltrexone. The effectiveness of treatment might vary based on patient characteristics. We hypothesized that causal machine learning would identify individualized treatment effects for each medication.

This is a secondary analysis of a multicenter randomized trial (CTN-0051, X:BOT) that compared the effectiveness of extended-release naltrexone versus buprenorphine-naloxone for preventing relapse of opioid misuse. Three machine learning models were derived using all trial participants with 50% randomly selected for training (n = 285) and the remaining 50% for validation. Individualized treatment effect was measured by the Qini value and c-for-benefit, with the absence of relapse denoting treatment success. Patients were grouped into quartiles by predicted individualized treatment effect to examine differences in characteristics and the observed treatment effects.

The best-performing model had a Qini value of 4.45 (95% confidence interval, 1.02–7.83) and a c-for-benefit of 0.63 (95% confidence interval, 0.53–0.68). The quartile most likely to benefit from buprenorphine-naloxone had a 35% absolute benefit from this treatment, and at study entry, they had a high median opioid withdrawal score (P < 0.001), used cocaine on more days over the prior 30 days than other quartiles (P < 0.001), and had highest proportions with alcohol and cocaine use disorder (P = 0.02). Quartile 4 individuals were predicted to be most likely to benefit from extended-release naltrexone, with the greatest proportion having heroin drug preference (P = 0.02) and all experiencing homelessness (P < 0.001).

Conclusions: Causal machine learning identified differing individualized treatment effects between medications based on characteristics associated with preventing relapse.

Related protocols: CTN-0051

Abstract:

This study aimed to estimate health state utility values (HSUVs) for the key health states found in opioid use disorder (OUD) cost-effectiveness models in the published literature. Data were obtained from six trials representing 1,777 individuals with OUD in the NIDA Clinical Trials Network (CTN-0001, -0002, -0009. -0030, -0049, and -0051). Researchers implemented mapping algorithms to harmonize data from different measures of quality of life (the SF-12 Versions 1 and 2 and the EQ-5D-3 L). They performed a regression analysis to quantify the relationship between HSUVs and the following variables: days of extra-medical opioid use in the past 30 days, injecting behaviors, treatment with medications for OUD, HIV status, and age. A secondary analysis explored the impact of opioid withdrawal symptoms.

There were statistically significant reductions in HSUVs associated with extra-medical opioid use (-0.002 (95% CI [-0.003,-0.0001]) to -0.003 (95% CI [-0.005,-0.002]) per additional day of heroin or other opiate use, respectively), drug injecting compared to not injecting (-0.043 (95% CI [-0.079,-0.006])), HIV-positive diagnosis compared to no diagnosis (-0.074 (95% CI [-0.143,-0.005])), and age (-0.001 per year (95% CI [-0.003,-0.0002])). Parameters associated with medications for OUD treatment were not statistically significant after controlling for extra-medical opioid use (0.0131 (95% CI [-0.0479,0.0769])), in line with prior studies. The secondary analysis revealed that withdrawal symptoms are a fundamental driver of HSUVs, with predictions of 0.817 (95% CI [0.768, 0.858]), 0.705 (95% CI [0.607, 0.786]), and 0.367 (95% CI [0.180, 0.575]) for moderate, severe, and worst level of symptoms, respectively.
Conclusions: Researchers for this study observed HSUVs for OUD that were higher than those from previous studies that had been conducted without input from people living with the condition.

Related protocols: CTN-0001, CTN-0002, CTN-0009, CTN-0030, CTN-0049, CTN-0051

Abstract:

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

Abstract:

No existing model allows clinicians to predict whether patients might return to opioid use in the early stages of treatment for opioid use disorder. The goal of this study was to develop an individual-level prediction tool for risk of return to use in opioid use disorder.

This decision analytical model (CTN-0094) 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 (CTN-0027 [START], CTN-0030 [POATS], and CTN-0051 [X:BOT]). 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.

All participants received 1 of 3 medications for opioid use disorder: methadone, buprenorphine, or extended-release naltrexone. 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.

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: 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.

Related protocols: CTN-0027, CTN-0030, CTN-0051, CTN-0094

Abstract:

Understanding the mechanisms of action of interventions is a major general goal of scientific inquiry. The collection of statistical methods that use data to achieve this goal is referred to as mediation analysis. Natural direct and indirect effects provide a definition of mediation that matches scientific intuition, but they are not identified in the presence of time-varying confounding. Interventional effects have been proposed as a solution to this problem, but existing estimation methods are limited to assuming simple (e.g., linear) and unrealistic relations between the mediators, treatments, and confounders. We present an identification result for interventional effects in a general longitudinal data structure that allows flexibility in the specification of treatment-outcome, treatment-mediator, and mediator-outcome relationships. Identification is achieved under the standard no-unmeasured-confounders and positivity assumptions.

In this article, we study semi-parametric efficiency theory for the functional identifying the mediation parameter, including the non-parametric efficiency bound, and was used to propose non-parametrically efficient estimators. Implementation of our estimators only relies on the availability of regression algorithms, and the estimators in a general framework that allows the analyst to use arbitrary regression machinery were developed. The estimators are doubly robust, sqrt(n)-consistent, asymptotically Gaussian, under slow convergence rates for the regression algorithms used. This allows the use of flexible machine learning for regression while permitting uncertainty quantification through confidence intervals and p-values. A free and open-source R package implementing the methods is available on GitHub. The proposed estimator to a motivating example from a trial of two medications for opioid-use disorder was applied (CTN-0051, the X:BOT study), where we estimate the extent to which differences between the two treatments on risk of opioid use are mediated by craving symptoms.

Related protocols: CTN-0051

Abstract:

Objectives: Timeline follow-back (TLFB) is a self-report measure commonly used as a method of assessing historical drug use in both clinical and research settings. Our study considered rates of agreement between TLFB and an objective biological assay of opioid use.

Methods: We calculated the rates of agreement between negative report of opioid use for the most recent 8 days on TLFB and urine toxicology (UTOX) results in a large multisite opioid use disorder treatment trial (CTN-0051, X:BOT).

Results: In total, 3986 assessments were provided by trial participants with both UTOX and TLFB during weeks 1 to 12, 2716 during weeks 13 to 24, and 325 at week 28. Rates of disagreement between negative TLFB and positive opioid UTOX were 2.33% of all assessments (21.68% of those with positive UTOX) over weeks 1 to 12, 2.06% of all assessment (25.00% of those with positive UTOX) over weeks 13 to 24, and 9.85% of all assessments (26.02% of those with positive UTOX) at week 28.

Conclusions: Negative TLFB seems to be generally associated with negative results on urine toxicology.

Related protocols: CTN-0051

Abstract:

Background and objectives: Limited research has explored sex differences in opioid use disorder medication (MOUD) treatment outcomes. The purpose of this study was to examine MOUD initiation onto buprenorphine-naloxone (BUP-NX) versus extended-release naltrexone (XR-NTX) by sex, and sex differences in clinical and psychosocial outcomes.

Methods: Using data from a 24-week open-label comparative effectiveness trial of BUP-NX or XR-NTX (CTN-0051, X:BOT), this study examined MOUD initiation (i.e., receiving a minimum one XR-NTX injection or first BUP-NX dose) and 24-week self-report outcomes. We used regression models to estimate the probability of MOUD initiation failure among the intent-to-treat sample (N = 570), and the main and interaction effects of sex on outcomes of interest among the subsample of participants who successfully initiated MOUD (n = 474).

Results: In the intent-to-treat sample, the odds of treatment initiation failure were not significantly different by sex. In the subsample of successful MOUD initiates, the effect of treatment on employment at week 24 was significantly moderated by sex (p = .003); odds of employment were not significantly different among males by MOUD type; females randomized to XR-NTX versus BUP-NX had 4.63 times greater odds of employment (p < .001). Males had significantly lower odds of past 30-day exchanging sex for drugs versus females (adjusted odds ratios [aOR] = 0.10, p = .004), controlling for treatment and baseline outcomes.

Discussion and conclusions: Further research should explore how to integrate employment support into OUD treatment to improve patient outcomes, particularly among women.

Scientific significance: The current study addressed gaps in the literature by examining sex differences in MOUD initiation and diverse treatment outcomes in a large, national sample.

Related protocols: CTN-0051

Abstract:

Objective: This study evaluated the association between medication for opioid use disorder (MOUD) and health care utilization over time among a sample of treatment-seeking individuals with opioid use disorder. In contrast to previous studies, this study used a novel measure of MOUD adherence, more comprehensive utilization data, and analyses that controlled for detailed individual and social determinants of health.

Methods: This study was a secondary analysis of a comparative effectiveness trial (N=570) of extended-release naltrexone versus buprenorphine-naloxone (CTN-0051, X:BOT). The outcome of interest was usage of nonstudy acute care, inpatient and outpatient addiction services, and other outpatient services across 36 weeks of assessment. Adherence (percentage of days taking MOUD) was defined as low (<20%), medium (=20% but <80%), or high (=80%). A two-part model evaluated the probability of utilizing a resource and the quantity (utilization days) of the resource consumed. A time-varying approach was used to examine the effect of adherence in a given month on utilization in the same month, with analyses controlling for a wide range of person-level characteristics.

Results: Participants with high adherence (vs. low) were significantly less likely to use inpatient addiction (p<0.001) and acute care (p<0.001) services and significantly more likely to engage in outpatient addiction (p=0.045) and other outpatient (p=0.042) services.

Conclusions: These findings reinforce the understanding that greater MOUD adherence is associated with reduced usage of high-cost health services and increased usage of outpatient care. The results further suggest the need for enhanced access to MOUD and for interventions that improve adherence.

Related protocols: CTN-0051