Aims: The aim of this study was to identify longitudinal trajectories of medication for opioid use disorder (MOUD) use throughout 1 year following MOUD initiation and to examine the association of trajectory membership with HIV testing among people who inject drugs in India.
Design, Setting And Participants: The study comprised group-based trajectory modeling using longitudinal clinic-based MOUD use data, set in seven Indian cities with integrated care centers (ICC) delivering MOUD, predominantly buprenorphine, in 2018-2019. A total of 1562 people who inject drugs who initiated MOUD for the first time at an ICC between 1 January 2018 and 31 December 2018 were included in this study. Median age was 26 years, 98% were male and 22% were living with HIV.
Measurements: Daily directly observed MOUD visits were biometrically verified and entered into an electronic database. A dichotomous variable for MOUD use each day throughout 1 year following initiation was created for the trajectory models. Client socio-demographics, HIV status and testing at the ICC and dose were extracted from the clinical database.
Findings: We found five MOUD trajectory groups: (1) early dropout (41%), (2) late dropout (18%), (3) delayed dropout (10%), (4) intermittent use (12%) and (5) persistent use (19%). Differences between the dropout groups were characterized by the rate of decline in MOUD use over time. The late dropout group had an 18% higher rate of HIV testing [adjusted rate ratio (aRR) = 1.18, 95% confidence interval (CI) = 1.10-1.27] and those with persistent MOUD use had a 91% higher rate of testing (aRR = 1.91, 95% CI = 1.77-2.05) compared with the early dropout group.
Conclusions: Nearly 70% of clients initiating medication for opioid use disorder (MOUD) at integrated care centers (ICCs) in India stop MOUD use within 1 year, with trajectories characterized by the rate of decline in engagement. Clients with better MOUD adherence appear to return more frequently for HIV testing at the ICCs, underscoring the value of integrated care models.
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http://dx.doi.org/10.1111/add.16713 | DOI Listing |
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