Doravirine plus lamivudine two-drug regimen as maintenance antiretroviral therapy in people living with HIV: a French observational study.

BACKGROUND: Two-drug regimens based on integrase strand transfer inhibitors (INSTIs) and boosted PIs have entered recommended ART. However, INSTIs and boosted PIs may not be suitable for all patients. We aimed to report our experience with doravirine/lamivudine as maintenance therapy in people living with HIV (PLWH) followed in French HIV settings. METHODS: This observational study enrolled all adults who initiated doravirine/lamivudine between 1 September 2019 and 31 October 2021, in French HIV centres participating in the Dat'AIDS cohort. The primary outcome was the rate of virological success (plasma HIV-RNA < 50 copies/mL) at Week (W)48. Secondary outcomes included: rate of treatment discontinuation for non-virological reasons, evolution of CD4 count and CD4/CD8 ratio over follow-up. RESULTS: Fifty patients were included, with 34 (68%) men; median age: 58 years (IQR 51-62), ART duration: 20 years (13-23), duration of virological suppression: 14 years (8-19), CD4 count: 784 cells/mm3 (636-889). Prior to switching, all had plasma HIV-RNA < 50 copies/mL. All but three were naive to doravirine, and 36 (72%) came from a three-drug regimen. Median follow-up was 79 weeks (IQR 60-96). Virological success rate at W48 was 98.0% (95% CI 89.4-99.9). One virological failure occurred at W18 (HIV-RNA = 101 copies/mL) in a patient who briefly discontinued doravirine/lamivudine due to intense nightmares; there was no resistance at baseline and no resistance emergence. There were three strategy discontinuations for adverse events (digestive disorders: n = 2; insomnia: n = 1). There was no significant change in CD4/CD8 ratio, while CD4 T cell count significantly increased. CONCLUSIONS: These preliminary findings suggest that doravirine/lamivudine regimens can maintain high levels of viral suppression in highly ART-experienced PLWH with long-term viral suppression, and good CD4+ T cell count.

How to Identify Potential Candidates for HIV Pre-Exposure Prophylaxis: An AI Algorithm Reusing Real-World Hospital Data.

HIV Pre-Exposure Prophylaxis (PrEP) is effective in Men who have Sex with Men (MSM), and is reimbursed by the social security in France. Yet, PrEP is underused due to the difficulty to identify people at risk of HIV infection outside the "sexual health" care path. We developed and validated an automated algorithm that re-uses Electronic Health Record (EHR) data available in eHOP, the Clinical Data Warehouse of Rennes University Hospital (France). Using machine learning methods, we developed five models to predict incident HIV infections with 162 variables that might be exploited to predict HIV risk using EHR data. We divided patients aged 18 or more having at least one hospital admission between 2013 and 2019 in two groups: cases (patients with known HIV infection in the study period) and controls (patients without known HIV infection and no PrEP in the study period, but with at least one HIV risk factor). Among the 624,708 admissions, we selected 156 cases (incident HIV infection) and 761 controls. The best performing model for identifying incident HIV infections was the combined model (LASSO, Random Forest, and Generalized Linear Model): AUC = 0.88 (95% CI: 0.8143-0.9619), specificity = 0.887, and sensitivity = 0.733 using the test dataset. The algorithm seems to efficiently identify patients at risk of HIV infection.