Cohort Profile: A European Multidisciplinary Network for the Fight against HIV Drug Resistance (EuResist Network)

Barbara Rossetti*, Francesca Incardona, Giulia Di Teodoro, Chiara Mommo, Francesco Saladini, Rolf Kaiser, Anders Sönnerborg, Thomas Lengauer, Maurizio Zazzi, EuResist Network, INTEGRATE study group, Carole Seguin-Devaux

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)

Abstract

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.
Original languageEnglish
Article number243
JournalTropical Medicine and Infectious Disease
Volume8
Issue number5
DOIs
Publication statusPublished - 23 Apr 2023

Keywords

  • HIV
  • HIV subtypes
  • antiretroviral therapy
  • drug resistance
  • treatment-response prediction system

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