Examination of Correlates of OUD Outcomes in Young Adults: Secondary Analysis From the XBOT Trial

Abstract

Background and Objectives: Opioid use disorder (OUD) treatment outcomes are poorer for young adults than older adults. Developmental differences are broadly implicated, but particular vulnerability factor interactions are poorly understood. This study sought to identify moderators of OUD relapse between age groups. Methods: This secondary analysis compared young adults (18-25) to older adults (26+) from a comparative effectiveness trial ("XBOT") that randomized (N = 570) participants to extendedrelease naltrexone or sublingual buprenorphine-naloxone. We explored the relationship between 25 prespecified patient baseline characteristics and relapse to regular opioid use by age group and treatment condition, using logistic regression. Results: Young adults (n = 111) had higher rates of 24-week relapse than older adults (n = 459) (70.3% vs 58.8%) and differed on a number of specific characteristics, including more smokers, more intravenous opioid use, and more cannabis use. No significant moderators predicted relapse, in either three-way or two-way interactions. Conclusions and Scientific Significance: No baseline factors were identified as moderating the relationship between age group and opioid relapse, nor any interactions between baseline characteristics, age group, and treatment condition to predict opioid relapse. Poorer treatment outcomes for young adults are likely associated with multiple developmental vulnerabilities rather than any single predominant factor. Although not reaching significance, several characteristics (using heroin, smoking tobacco, high levels of depression/anxiety, or treatment because of family/friends) showed higher odds ratio point estimates for relapse in young adults than older adults. This is the first study to explore moderators of worse OUD treatment outcomes in young adults, highlighting the need to identify predictor variables that could inform treatment enhancements. (Am J Addict 2021;30:433-444) ABBREVIATIONS BUP-NX buprenorphine naloxone ITT intent to treat MOUD medications for opioid use disorder OUD opioid use disorder SUD substance use disorder XBOT XR-NTX extended-release naltrexone

Application of The Consolidated Framework for Implementation Research to inform understanding of barriers and facilitators to the implementation of opioid and naloxone training on college campuses

“…Young adults are a priority population in the opioid overdose epidemic [ 16 – 18 ]. College-aged adults [ 18 – 25 ] are more likely than other age groups to misuse opioids generally (e.g., prescription pain reliever misuse or heroin use) and IMF specifically, and have worse OUD treatment outcomes (e.g., higher rates of 24-week relapse than older adults) [ 13 , 19 , 20 ]. Based on national CDC data, between 1999 and 2018 opioid-only and polysubstance-involved opioid overdose deaths (primarily involving synthetic opioids and cocaine) among adolescents and young adults ages 13–25 increased by 384% and 760%, respectively [ 21 ].…”

Application of the Consolidated Framework for Implementation Research to Inform Understanding of Barriers & Facilitators to the Implementation of Opioid and Naloxone Training on College Campuses

“…A number of factors likely contributed to this exacerbation, including social isolation, job loss, worsening mental health, and lack of widespread access to mental healthcare, opioid use disorder (OUD) treatment, and harm reduction services (2, 5, 8,(10)(11)(12)(13)(14)(15).Young adults are a priority population in the opioid overdose epidemic (16-18). College-aged adults (18-25) are more likely than other age groups to misuse opioids generally (e.g., misuse of prescription pain relievers or use of heroin) and IMF speci cally, and have worse OUD treatment outcomes (e.g., higher rates of 24-week relapse than older adults) (13,19,20). Based on national CDC data, between 1999 and 2018 opioid-only and polysubstance-involved opioid overdose deaths (primarily involving synthetic opioids and cocaine) among adolescents and young adults ages 13-25 increased by 384% and 760%, respectively (21).…”