Abstract
Aim:
The aim of this study was to estimate how ongoing stimulant use affects return to illicit opioid use after initiation onto medication for opioid use disorder (MOUD).
Design:
This was a secondary analysis of pooled data from two clinical trials comparing buprenorphine (BUP-NX) and extended-release naltrexone (XR-NTX).
Setting:
Thirteen opioid treatment programs and HIV clinics across 10 states in the United States from 2014 to 2019 took part in this study.
Participants:
A total of 528 participants who initiated MOUD as part of trial participation were included. Nearly half (49%) were between 30 and 49 years of age, 69% were male and 66% were non-Hispanic White.
Measurements:
The primary outcome was first self-reported day of non-prescribed opioid use following MOUD initiation, and the exposure of interest was daily stimulant use (methamphetamine, amphetamines or cocaine). Both were defined using time-line follow-back. Among participants reporting at least 1 day of illicit opioid use, we also examined relapse to ongoing use, defined as (1) 7 days of continuous opioid use or (2) 4 consecutive weeks with self-reported opioid use, one or more positive urine drug screens (UDS) for opioids or one or more missing UDS.
Findings:
Forty-seven per cent of participants reported stimulant use following MOUD initiation, 58% returned to illicit opioid use and 66% of those relapsed to ongoing use. Stimulant use was strongly associated with increased risk of misusing opioids after MOUD initiation when measured daily [adjusted hazard ratio (aHR) = 9.23, 95% confidence interval (CI) = 6.80–12.50, P < 0.001] and over a 7-day period (aHR = 1.27 for each additional day, CI = 1.18–1.37, P < 0.001). Using stimulants weekly or more often was associated with increased likelihood of relapse to ongoing opioid use compared with less than weekly or no stimulant use (adjusted odds ratio = 2.30, CI = 1.05–5.39, P = 0.044).
Conclusions:
People initiated on medication for opioid use disorder who subsequently use stimulants appear to be more likely to return to and continue using non-prescribed opioids compared with those without stimulant use. The association appears to be stronger among patients who initiate buprenorphine compared with those who initiate extended-release naltrexone.
Keywords: Buprenorphine, extended-release naltrexone, medications for opioid use disorder, opioids, relapse, stimulants
INTRODUCTION
In the United States, the proportion of people with opioid use disorder (OUD) also reporting using stimulants [most commonly, methamphetamine (MA) or cocaine] has increased dramatically during the past two decades [1–4]. Survey results from more than 13 000 patients entering drug treatment for OUD nationally found that the proportion of patients who had used MA in the last month increased from 18.8% in 2011 to 34.2% in 2017 [2]. Regional increases can be even larger: a study from West Virginia found that the proportion of people with OUD with co-occurring MA use quadrupled from 12% in 2014 to 47% in 2018 [3], and one from Kings County, Washington found that rates of past 30-day injections of heroin and MA together rose from 10% in 2009 to 53% in 2017 [5].
These increases are closely linked with an overdose epidemic that is now responsible for more than 100 000 deaths annually, the highest figure ever [6]. According to the National Institute on Drug Abuse (NIDA), fatal overdoses involving both cocaine and opioids increased 5.6-fold between 1999 and 2019, and fatal overdoses involving both ‘psychostimulants with abuse potential’ (a category which is dominated by MA) and opioids increased 13.5-fold [7]. Not only is stimulant use an increasingly common comorbidity of opioid use, using stimulants and opioids together is associated with increased risk of overdose [1, 8, 9]. With the rapid increase in availability and use of synthetic opioids (mainly fentanyl), and their adulteration of the MA supply, co-use of MA and opioids is likely to become far deadlier: emerging data from the beginning of the COVID-19 pandemic showed deaths involving MA and synthetic opioids doubling in a single year (2019–20) [7].
Randomized controlled trials (RCTs) have established that medications for OUD (MOUD) are efficacious for the treatment of OUD [10, 11], including buprenorphine–naloxone (BUP-NX) and extended-release naltrexone (XR-NTX). Despite their efficacy, return to illicit opioid use remains common. In contrast, treatment options for stimulant use disorders remain limited; while behavioral interventions such as contingency management have been shown to be effective but are difficult to implement, no medications to treat stimulant use disorders have been approved by the US Food and Drug Administration (FDA) [12].
Even less research examines treatment options for patients who use both stimulants and opioids [13]. A number of factors suggest that this group faces particular challenges. Some people who use both substances report using stimulants to counteract some effects of opioids (e.g. to stay awake or even reverse an overdose) or using opioids to manage the side-effects of stimulants (e.g. to lessen the ‘come-down’ or to fall asleep) [2, 14, 15]. Thus, habituated use of both substances may increase the risk of return to opioid use when stimulants are used. Additionally, as stimulant use frequently occurs in social contexts where other forms of drug use are present, continued stimulant use may expose patients to potential triggers for return to opioid use. Little is known about the effects of stimulant use on MOUD initiation, retention and outcomes among patients with OUD. A systematic review showed negative effects of MA on retention on MOUD [16]. However, most of the included studies were limited by crude measures of stimulant and opioid outcomes, small sample sizes, confounding and statistical methods that did not account for the time-varying nature of drug use [16]. Additionally, few studies have directly examined the relationship between stimulant use and return to opioid use following MOUD treatment initiation.
The objectives of this study were to estimate the relationship between continued stimulant use following MOUD initiation and (1) time to first use of non-prescribed opioids and (2) subsequent risk of relapsing to ongoing opioid use. We hypothesized that people who continued to use stimulants following treatment initiation would be more likely to return to illicit opioid use. We also explored how the relationship between stimulant use and return to opioid use may differ between BUP-NX and XR-NTX. Although studies have found that BUP-NX and XR-NTX are both effective in successfully initiated patients [10], their differing mechanisms of action may modify the association with stimulant use. We hypothesized that, because it is a long-acting full opioid antagonist, XR-NTX would be more effective in preventing return to opioid use in the presence of continued stimulant use compared to BUP-NX.
METHODS
Data sources and participants
This analysis used a pooled sample from two National Drug Abuse Treatment Clinical Trials Network (CTN) RCTs designed to compare the effectiveness of XR-NTX and BUP-NX, CTN 0051 (X:BOT; 2014–17) and CTN 0067 (CHOICES; 2018–19) [11, 17]. A total of thirteen opiate treatment programs and HIV clinics across 10 states took part in the trials. CHOICES was approved by the Advarra Institutional Review Board, with participating sites deferring to its regulatory role, while each X:BOT site received local institutional review board (IRB) approval. All participants in both studies provided written informed consent prior to participation. Key information on each study, including inclusion/exclusion criteria and recruitment and enrollment data, are presented in Supporting information, Table S1. The studies shared many similarities, including similar aims, harmonized data collection instruments and the same amount of follow-up time, but there were some notable differences. X:BOT, a much larger trial, initiated participants onto MOUD in an inpatient medically supervised withdrawal setting, while CHOICES was conducted entirely in outpatient HIV clinics and limited to people living with HIV. Because of the outpatient setting, fewer patients successfully started MOUD treatment in CHOICES, especially in the XR-NTX group. We limited our analyses to patients who initiated BUP-NX or XR-NTX, defined as either receiving an XR-NTX injection or filling a prescription for BUP-NX. A small number of CHOICES participants who started methadone (n = 8) were excluded from the analysis.
Exposures and outcomes
Daily stimulant, benzodiazepine and alcohol use
Measures of daily, time-varying substance use were measured using time-line follow-back (TLFB). Participants were asked to recall at each study visit which drugs they had consumed since the previous visit. Participants completed TLFB assessments every 1–4 weeks; if assessments were missed, TLFB was extended to the last completed assessment. Stimulant use was defined as reported use of powder cocaine, crack cocaine or ‘amphetamine-type stimulants’, including methamphetamine, on the TLFB assessment. Time-varying benzodiazepine use was defined as reported use of benzodiazepines, and time-varying heavy alcohol use was defined as consumption of four to five or more alcoholic drinks on any given day for women/men.
Seven-day stimulant use
A second measure of time-varying stimulant use was defined as the number of days of the last 7 days that a patient reported stimulant use.
Urine drug screening for stimulant use
A final measure of time-varying stimulant use was defined using weekly (X:BOT) or monthly (CHOICES) urine drug screening results (UDS). UDS for methamphetamine, other amphetamines and cocaine were combined into an indicator variable for stimulant positivity. Associations between the three measures of stimulant use (TLFB daily, TLFB 7-day and UDS) and return to illicit opioid use were estimated in separate models.
Weekly drug use indicators
In addition to daily measures of stimulant, benzodiazepine and alcohol use, we created binary variables representing use of these substances weekly or more often during the following periods: randomization to MOUD initiation, initiation to first use of non-prescribed opioids (if such use occurs) and first use of opioids to end of study. Participants were coded as weekly users if they used the drug in question on at least 1 of every 7 days during each period.
Return to illicit opioid use
Two measures were created to assess patients’ return to illicit opioid use. The first, time to first day of illicit opioid use, was defined using the TLFB assessment as the first day after the day of MOUD initiation in which a participant reported using heroin, non-prescribed methadone or illicit opioid painkillers. The second measure, relapse to ongoing use, was measured among those who reported at least 1 day of illicit opioid use, following the definition of relapse from the original X:BOT study team [18]. Participants were considered to have experienced a relapse to ongoing use if one of the following conditions was met: (1) the participant reported using heroin, illicit methadone or non-prescribed opioid painkillers for 7 or more days in a row or (2) there were 4 consecutive weeks in which the participant reported using heroin, methadone or opioid painkillers for at least 1 day, tested positive for opioids in a UDS screen or missed a UDS screen.
Statistical analyses
Prior to analysis, participant demographics, characteristics and behaviors were summarized and compared by return to opioid use using χ2 and Mann–Whitney U-tests. Kaplan–Meier curves were used to visualize time to first day of illicit opioid use, stratified by stimulant use and type of MOUD. Day zero was defined as the day a participant initiated MOUD treatment (received a prescription for BUP-NX or an injection of XR-NTX); participants who did not return to illicit opioid use were censored on their last day of study participation (~24 weeks after randomization; an average of 160 days after treatment initiation), including those who dropped out (41 of 528 participants dropped out prior to 24 weeks without evidence of returning to illicit opioid use, with an average of 81 days of follow-up time). Aside from dropout, the rate of missing TLFB data was low: only 7% of participants had any incomplete data, and < 1% had more than 5 days of missing data over approximately 24 weeks.
The relationship between time-varying stimulant use (daily, 7-day and UDS, all in separate models) and first day of illicit opioid use was assessed with Cox proportional hazards models. The proportional hazards assumption was verified by examining plots and statistical tests of scaled Schoenfeld residuals. Then, among participants who reported at least 1 day of illicit opioid use, logistic regression was used to model the association between weekly stimulant use following first day of opioid use and relapse to ongoing use. Both models adjusted for study, age, gender, race/ethnicity, education, homelessness within the past 6 months, HIV status, tobacco use history and frequency of injecting drugs. Models also adjusted for benzodiazepine and heavy alcohol use as well as history of stimulant use: in the Cox model, time-varying benzodiazepine and heavy alcohol use were also included as covariates, and the logistic regression models controlled for the weekly benzodiazepine and heavy alcohol use indicators plus weekly stimulant use prior to first use of opioids following initiation. Covariates for each model were chosen a priori based on hypothesized causal relationships with stimulant use and risk of return to illicit opioid use.
To test our second hypothesis, that type of MOUD would moderate the relationship between stimulant use and return to illicit opioid use, we added interactions between MOUD type and time-varying stimulant use in the Cox models and weekly stimulant use after first use of opioids in the logistic regression model. We conducted statistical tests of interaction and computed estimates stratified by type of MOUD. Statistical analyses were conducted in R version 4.0.5 with the ‘survival’ and ‘emmeans’ packages; all statistical testing was two-sided at the level of significance of 0.05. Statistical analyses were not pre-registered.
RESULTS
Participants
Throughout the two trials, a total of 528 of 684 (77%) randomized participants were initiated onto either BUP-NX (311 of 338, 92%) or XR-NTX (217 of 346, 63%). In both trials, participants were less likely to successfully initiate XR-NTX than BUP-NX. Of the included participants, X:BOT contributed 461 of 528 participants and CHOICES contributed 67 of 528 participants. Nearly half of participants (49%) were aged between 30 and 49 years, 69% were male, 66% were White, 83% used tobacco every day, 28% had been homeless within the last 6 months, 16% were living with HIV and 67% reported daily injection drug use. Only 11% of participants reported any stimulant use during the period between randomization and MOUD initiation, but 47% reported simulant use after initiation [mean number of days of stimulant use = 12, standard deviation (SD) = 26 days]. Table 1 presents participant characteristics overall and by return to illicit opioid use.
TABLE 1.
Participant characteristics, overall and by return to illicit opioid use.
| Characteristic | Overall N = 528 n (%)/mean (SD) | Returned to illicit opioid use n = 308 | Did not return to illicit opioid use n = 221 | P-valuea |
|---|---|---|---|---|
| Protocol | 0.2 | |||
| X:BOT (CTN 0051) | 461 (87%) | 263 (85%) | 198 (90%) | |
| CHOICES (CTN 0067) | 67 (13%) | 45 (15%) | 23 (10%) | |
| Age (years) | 0.6 | |||
| 18–29 | 201 (38%) | 122 (40%) | 79 (36%) | |
| 30–49 | 260 (49%) | 149 (48%) | 112 (51%) | |
| 50+ | 67 (13%) | 37 (12%) | 30 (14%) | |
| Gender | 0.6 | |||
| Female | 164 (31%) | 93 (30%) | 71 (32%) | |
| Male | 364 (69%) | 215 (70%) | 150 (68%) | |
| Race/ethnicity | 0.016 | |||
| Black | 82 (16%) | 55 (18%) | 27 (12%) | |
| Hispanic/Latino | 81 (15%) | 57 (19%) | 25 (11%) | |
| Other | 15 (2.8%) | 9 (23%) | 6 (3%) | |
| White | 350 (66%) | 187 (61%) | 163 (74%) | |
| Tobacco use | 0.3 | |||
| Daily | 441 (83%) | 254 (82%) | 187 (85%) | |
| Some days | 57 (11%) | 38 (12%) | 19 (8%) | |
| None | 31 (6%) | 16 (6%) | 15 (7%) | |
| MOUD | < 0.001 | |||
| Buprenorphine | 312 (59%) | 210 (68%) | 102 (46%) | |
| Extended-release naltrexone | 217 (41%) | 98 (32%) | 119 (54%) | |
| Daily injection | 350 (67%) | 212 (69%) | 140 (63%) | 0.2 |
| Homeless in last 6 months | 147 (28%) | 93 (30%) | 55 (25%) | 0.2 |
| HIV seropositive | 82 (16%) | 53 (17%) | 29 (13%) | 0.2 |
| Any stimulant use after initiation | 248 (47%) | 187 (61%) | 60 (27%) | < 0.001 |
| Any stimulant use between randomization and initiation | 59 (11%) | 37 (12%) | 22 (10%) | 0.5 |
| Days of stimulant use after initiation | 12 (26) | 17 (31) | 5 (17) | < 0.001 |
| Days of opioid use after initiation | 23 (39) | 39 (45) | 0 | NA |
Abbreviations: NA, not available; SD, standard deviation.
Pearson’s χ2 test or Wilcoxon’s rank-sum test.
Return to illicit opioid use
Of 528 participants who initiated MOUD, 308 (58%) reported at least 1 day of illicit opioid use during the 24-week period following initiation (mean = 39 days of opioid use, SD = 45). Although participants initiating BUP-NX and those initiating XR-NTX were equally likely to report any stimulant use after MOUD initiation (47% in both groups, P = 0.8), those initiated onto BUP-NX were substantially more likely to report illicit opioid use following initiation than participants initiated onto XR-NTX, with 67% of BUP-NX participants reporting at least 1 day of use compared to 46% of XR-NTX participants (log-rank P < 0.001). Figure 1 displays Kaplan–Meier curves of cumulative incidence of return to illicit opioid use following initiation by type of MOUD and amount of stimulant use over the same period.
FIGURE 1.
Kaplan–Meier cumulative incidence of return to opioid use as a function of stimulant use, stratified by type of MOUD.
In the Cox model, daily time-varying stimulant use was associated with more than a ninefold increased risk of returning to illicit opioid use after MOUD initiation [adjusted hazard ratio (aHR) = 9.23, 95% confidence interval (CI) = 6.80–12.50, P < 0.001]. This indicates that, on any given day, a participant reporting stimulant use was more than nine times more likely to also report their first day of illicit opioid use compared to a participant not using stimulants. The strength of the relationship differed between BUP-NX and XR-NTX (interaction = P < 0.001). For participants initiated onto BUP-NX, the aHR was 13.07 (95% CI = 9.25–18.47, P < 0.001) and for XR-NTX, the aHR was 4.67 (95% CI = 2.81–7.76, P < 0.001).
Cumulative 7-day stimulant use also increased the risk of return to illicit opioids. Overall, each additional day of stimulant use in the past week was associated with a 27% increase in the risk of using non-prescribed opioids (aHR = 1.27, 95% CI = 1.18–1.37, P < 0.001). The relationship was again stronger for BUP-NX participants than XR-NTX participants (interaction = P < 0.001). For participants initiated onto BUP-NX, each day of stimulant use in the last week was associated with a 42% increase in the risk of illicit opioid use (aHR = 1.42, 95% CI = 1.29–1.56, P < 0.001), while there was limited evidence supporting a significant increase among those who initiated XR-NTX (aHR = 1.10, 95% CI = 0.95–1.28, P = 0.201).
UDS measurements of stimulant use showed a similar pattern; participants testing positive for stimulants were 2.8 times more likely to return to illicit opioid use (aHR = 2.80, 95% CI = 2.35–3.33, P < 0.001). However, the interaction between UDS stimulant use and type of MOUD was not significant (P = 0.3).
Table 2 and Figure 2 display HRs and 95% CIs for time to first illicit opioid use for each measure of stimulant use, stratified by MOUD type.
TABLE 2.
Hazard and odds ratios for the associations between stimulant use and (1) return to opioid use following initiation of medication for opioid use disorder (MOUD) and (2) relapse to ongoing opioid use.
| N (%) | Daily stimulant use aHR (95% CI); P-value | 7-day stimulant use aHR (95% CI); P-value | Urine drug screen stimulant use aHR (95% CI); P-value | Weekly stimulant use aOR (95% CI); P-value | |
|---|---|---|---|---|---|
| Return to opioid usea | |||||
| Overall | 308/528 (58%) | 9.23 (6.80–12.5); < 0.001 | 1.27 (1.18–1.37); < 0.001 | 2.80 (2.35–3.33); < 0.001 | NA |
| BUP-NX | 208/XXX (67%) | 13.07 (9.25–18.47); < 0.001 | 1.42 (1.29–1.56); < 0.001 | 2.91 (2.41–3.53); < 0.001 | NA |
| XR-NTX | 100/XXX (46%) | 4.67 (2.81–7.76); < 0.001 | 1.10 (0.95–1.28); 0.201 | 2.33 (1.59–3.41); < 0.001 | NA |
| Relapse to ongoing opioid useb | |||||
| Overall | 204 (39%) | NA | NA | 2.30 (1.05–5.39); 0.044 | |
| BUP-NX | 141 (45%) | NA | NA | 3.72 (1.20–11.51); 0.022 | |
| XR-NTX | 63 (29%) | NA | NA | 1.27 (0.40–4.03); 0.684 | |
Abbreviations: aHR, adjusted hazard ratio; aOR, adjusted odds ratio; BUP, buprenorphine; CI, confidence interval; NA, not available; NTX, extended-release naltrexone.
Defined using the time-line follow-back as the first day after the day of MOUD initiation in which a participant reported using heroin, non-prescribed methadone or illicit opioid painkillers.
Among those who returned to opioid use, participants were considered to have experienced a relapse to ongoing use if one of the following conditions was met: (1) the participant reported using heroin, illicit methadone or non-prescribed opioid painkillers for 7 or more days in a row or (2) there were 4 consecutive weeks in which the participant reported using heroin, methadone or opioid painkillers for at least 1 day, tested positive for opioids in a urine drug screen or missed a drug screen.
FIGURE 2.
Adjusted hazard and odds ratios of (a) return to opioid use as a function of daily stimulant use, (b) return to opioid use as a function of cumulative stimulant use over a 7-day period and (c) relapse to ongoing stimulant use as a function of frequency of stimulant use following first opioid use after MOUD initiation (weekly or more often versus less than weekly or none). aHR = adjusted hazard ratio; aOR = adjusted odds ratio; BUP = buprenorphine; NTX = extended-release naltrexone; MOUD = medication for opioid use disorder.
Relapse to ongoing opioid use
Of the 308 participants who used non-prescribed opioids at least once following MOUD initiation, 204 met the criteria for a return to ongoing use (66%). Participants who reported using stimulants weekly or more often following their first use of opioids had 2.3 times greater odds of relapsing to ongoing use (aOR = 2.30, 95% CI = 1.05–5.39, P = 0.044). Although the interaction did not meet the threshold for statistical significance (P = 0.2), the adjusted odds ratio (aOR) of return to ongoing use was larger for BUP-NX participants (aOR = 3.72, 95% CI = 1.20–11.51, P = 0.022) than for XR-NTX participants (aOR = 1.27, 95% CI = 0.40–4.03, P = 0.684) (Table 2; Figure 2).
DISCUSSION
Our study found that stimulant use following MOUD treatment initiation may substantially increase the risk of return to illicit opioid use. Using stimulants on a given day was associated with a ninefold increase in the risk of returning to opioid use on that day, with risk cumulatively increasing as stimulants were used more frequently. Furthermore, among participants who used non-prescribed opioids after initiating treatment, those who were also using stimulants at least once a week were substantially more likely to relapse to ongoing illicit opioid use. Although risk of return to use was elevated for participants using either type of MOUD, it was substantially higher for BUP-NX compared to XR-NTX.
Our findings are supported by previous research showing that co-use of stimulants and opioids creates particular challenges for MOUD treatment and has been linked with lower levels of initiation and higher rates of return to opioid use and overdose [1, 8, 16]. However, existing work on the relationship between stimulant use and MOUD outcomes has relied upon cross-sectional exposure and outcome assessments, suboptimal measurements derived from medical charts with low sensitivity/specificity to detect drug use or relatively infrequent UDS results, all of which could result in significant exposure misclassification. Additionally, previous studies have not adjusted for other substance use, which may have resulted in substantial confounding [16]. Our study advances understanding by utilizing rich TLFB assessments, yielding a daily, time-varying understanding of how participants used drugs after their initiation onto MOUD. Although the data are self-reported, meta-analyses have shown more than 90% agreement between TLFB and biological measures of opioid use [19]. The TLFB data also allowed us to show that that stimulant use within the past week has a cumulative association with participants’ first misuse of opioids, suggesting that those with more frequent recent stimulant use are at higher risk than those with more sporadic stimulant use. We supplemented our TLFB analyses with time-varying UDS results, which supported elevated risk of return to illicit opioid use among people testing positive for stimulants.
Although participants’ first day of opioid misuse creates the possibility for a full return to use disorder, this outcome is not guaranteed and there is an important clinical difference between a participant who has a few days of opioid use following initiation and a participant who returns to frequent use of opioids. An analysis that only examines whether participants report any opioid use following initiation collapses this distinction and misses the factors that produce the more serious forms of relapse. To address this, we analyzed the sample of participants who reported any opioid use following initiation and grouped participants by the frequency of their stimulant use. We found that these participants’ odds of experiencing a relapse to ongoing opioid use—defined using both TLFB and UDS data as well as study dropout—were two-and-a-half times higher if they reported using stimulants at least weekly in the period following their first day of opioid misuse. This finding suggests that stimulants do, in fact, increase the risk of relapse to opioid use disorder or other consequences associated with frequent use.
Individually and together, our analyses provide evidence that stimulant use following MOUD initiation may be a major risk factor for return to opioid use. In all three models, this relationship was stronger for participants initiated onto BUP-NX than those initiated onto XR-NTX. Our study is subject to limitations, however, and several questions merit further examination. First, although this study demonstrates a strong relationship between stimulant use and return to opioid use following MOUD initiation, the reasons for this association remain unclear. Participants who used stimulants after initiation may be doing so in an environment where opioids are also present, or participants could be using opioids to manage the side effects of stimulant use. It is also possible that people who use both stimulants and opioids differ from those who use opioids but not stimulants in ways that are difficult to capture with statistical adjustment. Users of both substances could be those with more severe SUDs with increased risk of relapse; we adjusted for other substances use (benzodiazepines and heavy alcohol use) and frequency of injection drug use to mitigate this potential confounding effect. Regardless of whether the results we observe are causal effects of stimulant use or merely associations, our results suggest that people engaging in MOUD treatment who also use stimulants may benefit from more intensive clinical and behavioral support. Secondly, while we found evidence for a reduced association between stimulant use and return to opioid use among XR-NTX participants compared to BUP-NX participants, it is not clear if this difference is offset by the increased difficulty of initiation onto XR-NTX and patient preference for agonist-based therapy. Additionally, the two clinical trials utilized in this study, X:BOT and CHOICES, were conducted from 2014 to 2019, prior to the steep rise of fentanyl and methamphetamine as increasingly common forms of opioid and stimulant use. This means that the illicit opioids used by participants were mainly heroin or prescription painkillers and the dominant form of stimulant use was cocaine (although methamphetamine was not uncommon). Similar research conducted using more recent samples should be conducted to assess how widespread fentanyl and methamphetamine use might change the relationship between stimulant use and opioid relapse. Finally, these two trials were conducted in specialized populations—X:BOT in patients undergoing medically monitored withdrawal management and CHOICES in HIV clinics. Our results may not be generalizable to other settings, including individuals receiving office-based MOUD.
Although MOUD treatment saves lives, only approximately 30–50% of people initiating MOUD are retained long-term [20]. There are several significant barriers to treatment retention, including lack of access, stigma, cost, fragmented SUD care systems and a complex regulatory environment; our study suggests that ongoing stimulant use may also substantially increase the risk of opioid relapse and probably contribute to treatment discontinuation. Polysubstance use, especially the co-occurring use of psychostimulants and opioids, remains a substantial clinical challenge with few treatment options. Efforts to identify efficacious treatments for stimulant use disorders and integrate these treatments with OUD treatment should be intensified.
Supplementary Material
ACKNOWLEDGEMENTS
Research reported in this publication was supported by the National Institute on Drug Abuse of the National Institutes of Health under Award Number UG1DA015831. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. R.C. was supported by NIH/NIDA K01DA055130 and AHRQ/PCORI K12HS026370.
Funding information
National Institute on Drug Abuse, Grant/Award Numbers: K01DA055130, UG1DA015831; AHRQ/PCORI, Grant/Award Number: K12HS026370
Footnotes
DECLARATION OF INTERESTS
P.T.K. serves as principal investigator for NIH-funded studies that accept donated study medication from Indivior (buprenorphine) and Alkermes (extended-release naltrexone). Other authors declare that they have no competing interests.
CLINICAL TRIAL REGISTRATION
Data were drawn from two completed clinical trials, CTN 0051 ClinicalTrials.gov NCT02032433) and CTN 0067 (NCT03275350).
SUPPORTING INFORMATION
Additional supporting information can be found online in the Supporting Information section at the end of this article.
DATA AVAILABILITY STATEMENT
Data from CTN 0051 (X:BOT) and 0067 (CHOICES) are publicly available on the NIDA DataShare 2.0 website.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data from CTN 0051 (X:BOT) and 0067 (CHOICES) are publicly available on the NIDA DataShare 2.0 website.