Francesco Saladini

The EuResist cohort was established in 2006 with the purpose of developing a clinical decision-support tool predicting the most effective antiretroviral therapy (ART) for persons living with HIV (PLWH), based on their clinical and virological data. Further to continuous extensive data collection from several European countries, the EuResist cohort later widened its activity to the more general area of antiretroviral treatment resistance with a focus on virus evolution. The EuResist cohort has retrospectively enrolled PLWH, both treatment-naïve and treatment-experienced, under clinical follow-up from 1998, in nine national cohorts across Europe and beyond, and this article is an overview of its achievement. A clinically oriented treatment-response prediction system was released and made available online in 2008. Clinical and virological data have been collected from more than one hundred thousand PLWH, allowing for a number of studies on the response to treatment, selection and spread of resistance-associated mutations and the circulation of viral subtypes. Drawing from its interdisciplinary vocation, EuResist will continue to investigate clinical response to antiretroviral treatment against HIV and monitor the development and circulation of HIV drug resistance in clinical settings, along with the development of novel drugs and the introduction of new treatment strategies. The support of artificial intelligence in these activities is essential.

Background: Clinical trials have demonstrated noninferior viral suppression rates of selected 2-drug regimens (2DRs) over standard 3-drug regimens (3DRs). However, the effect of simplification to 2DRs on HIV-1 reservoir remains to be fully assessed. Setting: Retrospective analyses of samples of virologically suppressed people living with HIV remaining on the same 3DRs or switching to DTG + 3TC or ATV/r + 3TC 2DRs. Methods: Whole blood samples were collected at enrollment and after 48 weeks. Total HIV-1 DNA (tDNA) and intact HIV-1 DNA (iDNA) were quantified by droplet digital polymerase chain reaction and intact proviral DNA assay, respectively. Statistical analysis was performed to identify associations among variables, and multiple linear regression was used to analyze potential predictors of tDNA and iDNA changes over time. Results: Forty-seven individuals were switched to DTG + 3TC 2DR (N = 23) and ATV/r + 3TC 2DR (N = 24), while 18 remained on 3DRs. tDNA did not change either in the overall population or in the 3DR and 2DR groups. iDNA decreased significantly in the whole data set and in the overall 3DR and 2DR groups ( P = 0.001, P = 0.039 and P = 0.009, respectively). iDNA, but not tDNA, was inversely correlated with the time of viral suppression ( P = 0.002) and time under antiretroviral therapy ( P = 0.006). Higher nadir CD4 + T-cell counts ( P = 0.001) and lower zenith viral load ( P = 0.02) showed an association with the decrease of iDNA, but not with tDNA. Conclusions: Both tDNA and iDNA dynamics supported noninferior efficacy of 2DRs over 3DRs. iDNA could be more informative than tDNA in analyzing the dynamics of the HIV-1 reservoir under different treatment strategies.