CROI 2025 Abstract eBook

Abstract eBook

Poster Abstracts

The primary cohort consisted of 327,362 individuals as overall population, encompassing 1,524 confirmed HIV+ cases. The primary cohort was partitioned, with 70% allocated for model training and 30% for internal validation. A secondary cohort of 111,913 individuals served as an external validation set. An elastic net-regularized logistic regression model augmented with synthetic minority oversampling technique (SMOTE) was developed. The variables considered for model inclusion were specific age group (20-59 years old), sex and the presence of 59 HIV-associated conditions within the preceding five years as predictor variables. Results: The model obtained identified 10 clinical conditions with the highest predictive risk value (hepatitis A & C, gonococcus, syphilis, proctitis, urethritis, sexual contact, drug intoxication, candidiasis and condyloma acuminatum), 6 different age groups and sex. Demonstrated a training sensitivity and specificity of 82.96% and 64.54%, respectively. Validation across two populations (30% of first cohort and external validation) yielded sensitivity of 77.50% and 71.74%, with specificities of 64.05% and 65.51%. The HIV prevalence observed in all cohorts exceeded 2.6%. The number needed to test (NNT) to have one positive HIV diagnosis was between 12-48 individuals, depending on the different probability ranges identified (Table 1). Conclusions: The model identified over 70% of HIV cases using an EHR database, screening less than 4% of a health department size population and achieved a prevalence rate above 2.6%. This tool might represent a transformative solution for hidden HIV detection and help achieving the UNAIDS 95-95-95 target. Its ease of implementation and targeted approach appears to be promising to drastically reduce missed and late diagnoses, thereby significantly impacting the trajectory of the HIV epidemic.

1130 Examining PopART Intervention Impact on HIV in the General Populations of Zambia and South Africa

Bonnie Shook-Sa 1 , Paul N. Zivich III 1 , Stephen R. Cole 1 , Nora E. Rosenberg 1 , Deborah J. Donnell 2 , Sizulu Moyo 3 , Khangelani Zuma 3 , Joseph J. Eron 1 , Richard Hayes 4 , Jessie K. Edwards 1 1 University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, 2 Fred Hutchinson Cancer Center, Seattle, WA, USA, 3 Human Sciences Research Council, Pretoria, South Africa, 4 London School of Hygiene & Tropical Medicine, London, UK Background: PopART was a cluster randomized trial (CRT) designed to evaluate universal testing and treatment (UTT) strategies for HIV prevention. While CRTs are the gold standard for evaluating population-level effects, they can be subject to selection bias when those enrolled differ from the population of interest. PopART included two intervention arms: (A) combination prevention with universal antiretroviral therapy (ART) for individuals with HIV, (B) combination prevention with ART based on local guidelines. Both included universal HIV testing and were compared to the third arm, standard of care (SOC). Interventions were conducted in entire randomized communities; their impact was measured on a sampled population cohort (PC). Unexpectedly, arm A did not have significantly lower HIV incidence. This may be due to differences between PC participants and the population of interest. For example, men were 46% of the population of interest but only 32% of the PC. Methods: We generalize PopART findings to a population of interest, 4.5 million adults aged 18-44 in 5 PopART provinces represented by 2 probability based surveys: the 2016 Zambia Population-based HIV Impact Assessment and the 2017 South African National HIV Prevalence, Incidence, Behaviour and Communication Survey (ZAMPHIA/SABSSM). PC participants were weighted to estimate risk of HIV infection in trial arms in the population of interest over 3 years; risk in intervention arms was compared to SOC. Weighting accounted for key demographic and HIV risk factors, including sex, male circumcision, and age. Weighted estimates were compared to unweighted estimates. Results: With weighting, risk of HIV infection in the population of interest is lower in all arms (Figure). Arm A risk between 1-3 years is slightly higher than SOC in the unweighted analysis (Risk Difference [RD]: 0.10%; 95% CI: -1.15%, 1.25%), but lower than SOC with weighting (RD: -0.34%; 95% CI: -2.04% to 0.96%). The effect of arm B relative to SOC is in the same direction for both approaches, but weighting nearly doubled the estimated effect size (unweighted RD: -0.66%, 95% CI: -1.88% to 0.46%; weighted RD: -1.18%, 95% CI: -2.85% to 0.15%). Differences in estimates are likely due to effect heterogeneity between subgroups that were disproportionately included in the PC sample. Conclusions: Interventions were more protective in the population of interest than in the PC sample. Appropriate representation of subgroups is essential for guiding decisions from community-based trials.

Poster Abstracts

1129 WITHDRAWN

1131 Addressing Advanced HIV Disease: Insights on CD4 Testing and AHD Prevalence at PEPFAR Sites Gabriel Saemisch 1 , Karishma Srikanth 1 , Thomas Minior 1 , Jessica Stephens 1 , Deidra Parrish 1 , Nelly Maina 2 , Samantha Serrano 1 1 United States Agency for International Development, Washington, DC, USA, 2 Credence Management Solutions, LLC, Tysons Corner, VA, USA Background: Advanced HIV Disease (AHD) in individuals aged 5 and older is defined by a CD4 count below 200 cells/mm³ or World Health Organization (WHO) stage 3 or 4 conditions. Despite the global shift to a test-and-treat

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