CROI 2025 Abstract eBook

Abstract eBook

Poster Abstracts

1327 Heterogeneity of Disengagement From Antiretroviral Care Matters for Treatment Success Claire M. Keene 1 , Jonathan Euvrard 2 , Aaloke Mody 3 , Scott Colwell 4 , Tali Cassidy 2 , Jacob McKnight 1 , Mike English 1 , Ingrid Katz 5 , Catherine Orrell 2 1 University of Oxford, Oxford, UK, 2 University of Cape Town, Cape Town, South Africa, 3 Washington University in St Louis, St Louis, MO, USA, 4 University of Guelph, Guelph, ON, Canada, 5 Harvard Medical School, Boston, MA, USA Background: Disengagement from antiretroviral treatment undermines HIV programme success. Current approaches targeting interventions at specific demographic groups miss most people out of care. Classifying patterns of engagement could use precision public health principles to identify unique care needs, and inform service development targeted at patients with similar experiences. Methods: Using routine health data from the Western Cape Provincial Health Data Centre, South Africa, we analysed individuals ≥15 years old who initiated treatment after 01-Sep-2016, sought care in low-resource, high-HIV burden settings, and had ≥5 years follow-up before database closure (30-Sep 2022). Group-based trajectory-modelling identified subgroups with distinct longitudinal engagement patterns from initiation (disengagement defined using pharmacy refill data as a treatment interruption >90 days). We assessed subgroup associations with viral suppression ≤1000 copies/mL with logistic regression. Results: This cohort included 26422 individuals: 71% female with median of age 31 years (IQR 26-38) at initiation. The best-fitting model identified five subgroups (figure): 1) Optimal engagement (38%); 2) Early disengagement (25%); 3) Delayed disengagement after two years (15%); 4) Disengagement with early return by two years (12%); and 5) Disengagement with delayed return by five years (10%). No variables were strongly predictive of subgroup membership, and subgroups were similar in age, sex, comorbidities, baseline CD4 count, regimen, and duration on treatment. All suboptimal patterns were strongly associated with lower odds of suppression at five years than the optimally engaged subgroup (adjusted odds ratios [95% confidence interval]: 0.05 [0.04-0.06], 0.15 [0.13-0.17], 0.64 [0.56-0.73], and 0.33 [0.29-0.39] for subgroups 2, 3, 4, and 5 respectively), with stronger associations compared to demographic and clinical variables. Conclusions: Disengagement was common, and most interrupted treatment (>90 days) within five years from initiation. However, engagement was not binary: people disengaged in various ways. Patterns of disengagement behaviour were more predictive of viral suppression than demographic or clinical factors, and could prove useful to target resources. It was difficult to predict subgroup membership with routine data, so further exploration of lived experiences behind each pattern could help identify what each subgroup needs to support sustained engagement, and facilitate more person-centred service delivery.

rather than initiating treatment for the first time. Understanding patterns of engagement after a substantial treatment interruption could help to direct service implementation and choice of interventions for this crucial population, and help make progress in controlling the epidemic. Methods: Using routine health data from the Western Cape Provincial Health Data Centre, South Africa, we analysed individuals ≥15 years old who initiated treatment after 01-Sep-2016, sought care in low-resource, high-HIV burden settings, and had ≥5 yearsfollow-up before database closure (30-Sep 2022). Group-based trajectory modelling identified subgroups with distinct longitudinal engagement patterns from the time of restarting therapy after a treatment interruption (disengagement defined using pharmacy refill data as a treatment interruption >90 days). Logistic regression assessed subgroup associations with viral suppression ≤1000 copies/mL. Results: The cohort (n=2150) was 71% female with median of age 30 years (IQR 25-36) at initiation. The best-fitting model identified five subgroups of engagement over five years after restart (figure): 1) Optimal engagement (30%); 2) Rapid disengagement (25%); 3) Early disengagement (16%); 4) Delayed disengagement (12%); and 5) Disengagement with return (17%). Nearly half (47%) disengaged again within the first year, but most (70%) disengaged again within five years of return. Subgroups were similar in age, sex, comorbidities, baseline CD4 count, and duration on treatment, with no variables strongly predictive of subgroup membership. Subgroups were strongly associated with lower odds of viral suppression at 5 years compared to the optimally engaged subgroup (adjusted odds ratio [95% confidence interval]: 0.09 [0.04-0.09], 0.11 [0.05-0.22], 0.16 [0.10-0.29] and 0.61 [0.39-0.97] for subgroups 2, 3, 4, and 5 respectively). Conclusions: Most people returning to care after a substantial treatment interruption disengaged again within five years from restart, with high rates of early drop out. However, disengagement followed a range of patterns with differing associations with viral suppression. These patterns may be useful to help target interventions to subgroups with similar engagement behaviours, but require further exploration to operationalise the patterns in the data and use these findings to inform decisions on service delivery.

Poster Abstracts

1329 Reasons for Discontinuation of Cabotegravir Long-Acting (CAB-LA) Among Clients in Zambia Damian J. Phiri 1 , Mutinta Nyumbu 1 , Adamson P. Ndhlovu 1 , Lackeby Kawanga 1 , Jemmy Musangulule 1 , Musonda Musonda 2 , Sarah Hatchard 1 1 John Snow, Inc, Lusaka, Zambia, 2 United States Agency for International Development, Washington, DC, USA Background: On 9th February, 2024, Zambia launched the use of Cabotegravir Long-Acting (CAB-LA) for HIV prevention, as an additional layer to oral PrEP The aim was to expand HIV prevention options for high-risk individuals and address challenges with oral PrEP such as inconsistent use due to pill burden, privacy issues and stigma. However, within 6 months of implementation discontinuation on CAB LA have also been experienced. Understanding discontinuation patterns and reasons is critical for optimizing adherence and improving program outcomes. This study aimed to review discontinuation patterns among clients initiated on CAB-LA. Methods: A cross sectional analysis was conducted on individuals initiated on CAB-LA between February and July 2024 in Kitwe and Chibombo districts. Discontinuation data, including the number and reasons for stopping CAB LA, were collected. Discontinuation reasons were categorized into nine groups:

1328 Patterns of Engagement After Restarting Antiretroviral Treatment in South Africa Claire M. Keene 1 , Jonathan Euvrard 2 , Aaloke Mody 3 , Scott Colwell 4 , Tali Cassidy 2 , Mike English 1 , Jacob McKnight 1 , Ingrid Katz 5 , Catherine Orrell 2 1 University of Oxford, Oxford, UK, 2 University of Cape Town, Cape Town, South Africa, 3 Washington University in St Louis, St Louis, MO, USA, 4 University of Guelph, Guelph, ON, Canada, 5 Harvard Medical School, Boston, MA, USA Background: As cycling in and out of HIV care over time becomes the norm for people with HIV, most commencing antiretroviral therapy are now restarting

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