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

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Title: Examination of Correlates of OUD Outcomes in Young Adults: Secondary Analysis From the XBOT Trial.
Authors: Fishman, Marc (AUTHOR), Wenzel, Kevin (AUTHOR), Scodes, Jennifer (AUTHOR), Pavlicova, Martina (AUTHOR), Campbell, Aimee N. C. (AUTHOR), Rotrosen, John (AUTHOR), Nunes, Edward (AUTHOR)
Source: American Journal on Addictions. Sep2021, Vol. 30 Issue 5, p433-444. 12p. 2 Charts, 1 Graph.
Subjects: Young adults, Older people, Age groups, Secondary analysis, Opioid abuse, Substance abuse relapse
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 extended‐release 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;00:1‐12) [ABSTRACT FROM AUTHOR]
Copyright of American Journal on Addictions is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Examination of Correlates of OUD Outcomes in Young Adults: Secondary Analysis From the XBOT Trial.
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  Data: <searchLink fieldCode="JN" term="%22American+Journal+on+Addictions%22">American Journal on Addictions</searchLink>. Sep2021, Vol. 30 Issue 5, p433-444. 12p. 2 Charts, 1 Graph.
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  Data: <searchLink fieldCode="DE" term="%22Young+adults%22">Young adults</searchLink><br /><searchLink fieldCode="DE" term="%22Older+people%22">Older people</searchLink><br /><searchLink fieldCode="DE" term="%22Age+groups%22">Age groups</searchLink><br /><searchLink fieldCode="DE" term="%22Secondary+analysis%22">Secondary analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Opioid+abuse%22">Opioid abuse</searchLink><br /><searchLink fieldCode="DE" term="%22Substance+abuse+relapse%22">Substance abuse relapse</searchLink>
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  Data: 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 extended‐release 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;00:1‐12) [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of American Journal on Addictions is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Sep2021
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