Abstract
Although opioid agonist therapy (OAT) is associated with positive health outcomes, including improved HIV management, long-term retention in OAT remains low among patients with opioid use disorder (OUD). Using data from the Veterans Aging Cohort Study (VACS), we identify variables independently associated with OAT retention overall and by HIV status. Among 7,334 patients with OUD, 13.7% initiated OAT, and 27.8% were retained 12-months later. Likelihood of initiation and retention did not vary by HIV status. Variables associated with improved likelihood of retention included receiving buprenorphine (relative to methadone), receiving both buprenorphine and methadone at some point over the 12-month period, or diagnosis of HCV. History of homelessness was associated with a lower likelihood of retention. Predictors of retention were largely distinct between patients with HIV and patients without HIV. Findings highlight the need for clinical, systems, and research initiatives to better understand and improve OAT retention.
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Acknowledgements
This work was supported by the National Institute on Alcohol Abuse and Alcoholism (R01 AA022886 (Kraemer) and U10 AA013566 (Justice)). Dr. Wyse’s time was supported by Career Development Award 1IK2HX003007 from the U.S. Department of Veterans Affairs Health Services Research and Development, K12HS026370 from the Agency for Healthcare Research and Quality and resources from the VA Health Services Research and Development-funded Center to Improve Veteran Involvement in Care at the VA Portland Health Care System (CIN 13-404). Dr. Korthuis’ time was supported by the National Institutes of Health, National Institute on Drug Abuse (UG3DA044831, UG1DA015815). Dr. Edelman’s time was supported by NIDA (R01DA040471). Dr. Crystal’s time was supported by NIDA (R01DA047347) and NCATS (UL1TR003017). A prior version of this research was presented at the College on Problems of Drug Dependence Annual Meeting, 2020. The authors have no relevant financial or non-financial interests to disclose.
Funding
This work was supported by the National Institute on Alcohol Abuse and Alcoholism (R01 AA022886 (Kraemer) and U10 AA013566 (Justice)). Dr. Wyse’s time was supported by Career Development Award 1IK2HX003007 from the U.S. Department of Veterans Affairs Health Services Research and Development, K12HS026370 from the Agency for Healthcare Research and Quality and resources from the VA Health Services Research and Development-funded Center to Improve Veteran Involvement in Care at the VA Portland Health Care System (CIN 13–404). Dr. Korthuis’ time was supported by the National Institutes of Health, National Institute on Drug Abuse (UG3DA044831, UG1DA015815). Dr. Edelman’s time was supported by NIDA (R01DA040471). Dr. Crystal’s time was supported by NIDA (R01DA047347) and NCATS (UL1TR003017).
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All authors contributed to the study conception and design. Material preparation and data collection and acquisition were performed by Kathleen McGinnis, Melissa Skanderson and Amy Justice. Analyses were run by Kathleen McGinnis. The first draft of the manuscript was written by Jessica Wyse and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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The authors have no relevant financial or non-financial interests to disclose. The content of this article is solely the responsibility of the authors and does not represent the official views of the Department of Veterans Affairs or the Agency for Healthcare Research and Quality.
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The study protocol was approved by the Institutional Review Boards of the University of Pittsburgh, VA Pittsburgh Healthcare System and VA Connecticut Healthcare System and the study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.
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A prior version of this research was presented at the College on Problems of Drug Dependence Annual Meeting, 2020.
Appendix
Appendix
To identify distinctive pattern of methadone treatment over time, as indicated by number of visit days (OTP/stop code 523 or inpatient) per month, we utilized group-based trajectory modeling. Trajectory modeling sorts each participant’s measurements (number of visits per month) into “clusters” and estimates distinct trajectories. The procedure calculates each individual’s probability of belonging to each trajectory group and assigns the individual to the trajectory with the highest probability of membership. We used months after start of treatment as the time scale. We used a normal model and evaluated a 4-trajectory group model. With methadone retention defined as 4 + visits/month to an OTP in the first month and 1 + visits/month in months 2–12, we calculated 12-month retention within each trajectory group as follows: 0% for group 1, 17% for group 2, 7% for group 3, and 75% for group 4.
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Wyse, J.J., McGinnis, K.A., Edelman, E.J. et al. Twelve-Month Retention in Opioid Agonist Treatment for Opioid Use Disorder Among Patients With and Without HIV. AIDS Behav 26, 975–985 (2022). https://doi.org/10.1007/s10461-021-03452-0
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DOI: https://doi.org/10.1007/s10461-021-03452-0