biostudies-literatureKizito SNICHD NIH HHS105753https://www.ebi.ac.uk/biostudies/studies/S-EPMC12930875biostudies-literatureUnknown244<h4>Objectives</h4>Adolescents living with HIV (ALHIV) have low viral suppression levels, with 1 in 3 ALHIV experiencing virologic failure, calling for more efforts to reverse these trends. We developed and validated a model that predicts the risk of virologic failure (VF) among ALHIV.<h4>Study design</h4>Cross-sectional study.<h4>Methods</h4>We used baseline data from 702 ALHIV enrolled in the Suubi + Adherence cluster-randomized clinical trial. Participants were aged 10-16 years, living with HIV and aware of their HIV status, and are living with a family. We developed a risk-prediction model for VF (viral load of ≥200 copies/mL) using sociodemographic, behavioral, psychological, economic, and treatment-related factors. LASSO logistic regression using 10-fold cross-validation with bootstrPublic healthA prediction model for virologic failure in adolescents living with HIV in Uganda: Findings from the Suubi+Adherence study.PMC12930875R01 HD074949Brownson RNamatovu PNabayinda JJohnson KJSsewamala FMKizito SNeilands TBNabunya PMcKay MMfalseA prediction model for virologic failure in adolescents living with HIV in Uganda: Findings from the Suubi+Adherence study.<h4>Objectives</h4>Adolescents living with HIV (ALHIV) have low viral suppression levels, with 1 in 3 ALHIV experiencing virologic failure, calling for more efforts to reverse these trends. We developed and validated a model that predicts the risk of virologic failure (VF) among ALHIV.<h4>Study design</h4>Cross-sectional study.<h4>Methods</h4>We used baseline data from 702 ALHIV enrolled in the Suubi + Adherence cluster-randomized clinical trial. Participants were aged 10-16 years, living with HIV and aware of their HIV status, and are living with a family. We developed a risk-prediction model for VF (viral load of ≥200 copies/mL) using sociodemographic, behavioral, psychological, economic, and treatment-related factors. LASSO logistic regression using 10-fold cross-validation with bootstr2025-01-01T00:00:00Z2025 Jul2026-07-09T12:23:48.239Z2026-07-09T11:17:48.469ZS-EPMC129308754036762210.1016/j.puhe.2025.105753