Antiretroviral resistance in at least second-line HIV-1 treatment virologic failure with common InSTI-based regimens
Year: 2025
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: To assess the prevalence and patterns of treatment-emergent resistance-associated mutations (RAMs) in people with HIV (PWH) with ≥1 prior regimen experiencing virologic failure (VF) with bictegravir/emtricitabine/tenofovir alafenamide (B/F/TAF), dolutegravir/lamivudine (DTG/3TC), or cabotegravir/rilpivirine (CAB + RPV) in an observational setting. DESIGN: A noninterventional, multicenter, retrospective, observational study was conducted between January 1, 2022 and December 31, 2024 using a national French multicenter database of genotypic resistance assays performed at confirmed VF. METHODS: VF was defined as 2 consecutive HIV-1 plasma viral loads of >50 copies/mL. Genotypic resistance assays were performed using Sanger sequencing. Treatment-emergent RAMs were characterized using the 2024 ANRS algorithm. Clinical history, virologic history, and demographic data were collected from medical records during standard clinical follow-up. RESULTS: A total of 6523 PWH were followed over 3 years. The prevalence of VF during follow-up was 6% with B/F/TAF, 5% with DTG/3TC, and 5% with CAB + RPV. The prevalence of treatment-emergent RAMs at VF were 3% with B/F/TAF, 15% with DTG/3TC, and 32% with CAB + RPV. Dual treatment-emergent integrase strand transfer inhibitor (InSTI) and nucleoside reverse transcriptase inhibitor (NRTI) RAMs were observed with B/F/TAF and DTG/3TC, while dual treatment-emergent nonnucleoside reverse transcriptase inhibitor (NNRTI) and InSTI RAMs were observed with CAB + RPV. CONCLUSIONS: The overall prevalence of VF was low for all regimens. B/F/TAF was associated with a numerically lower prevalence of RAMs at VF compared with DTG/3TC and CAB + RPV. These observational findings highlight the importance of monitoring resistance patterns to optimize HIV treatment outcomes.
Source: AIDS
Institutions: Inserm, Sorbonne Université, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Institut Pierre Louis d‘Épidémiologie et de Santé Publique, Gilead Sciences (United States), Gilead Sciences (France), Université Paris Cité, Hôpital Bichat-Claude-Bernard, Infection, Anti-microbiens, Modélisation, Evolution
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7117582564