Disclaimer

The system provides an estimate of in vivo efficacy of commonly used antiretroviral drug combinations based on user-defined information of HIV genotype (mandatory) and additional patient information (recommended). The engine is not intended as a replacement for standard of care but can be used by HIV specialists as an additional treatment decision support tool. Although analysis of a large data set of medical records has shown a good performance of the system, there is no warranty that its use will improve patient health. HIV care must rely on a solid knowledge of the complex host-virus interaction and proper consideration of patient status and commitment.



EuResist prediction system

The EuResist project has developed an integrated computational system for clinical management of antiretroviral drug resistance. The system requests HIV genotype and optionally a set of clinical data and returns a prediction of response to common antiretroviral regimens, helping the HIV specialist to choose the most effective drug combinations for her/his patient.

Nov 2010 update

The system has been re-trained and tested in November 2010 on a set of data derived from clinical practice records of more than 48,000 HIV patients collected in Europe. Among these, around 4% were treated with Recently Approved Compounds (RACs). The internal validation showed a prediction accuracy of 77-78% (AUROC) (66-69% on RACs) when treatment success was defined as achieving a decrease of at least 2 log or an undetectable HIV RNA load at week 8 after treatment start. read more.

The EuResist system is a linear combination of three statistical learning engines predicting response to treatment. These were designed to work with viral genotype and intended regimen as the only information, as well as with additional measurements (e.g. baseline viral load) and information derived from previous treatments and genotypes to enhance prediction performance. The models combined in the final prediction system include: a Generative Discriminative engine using a Bayesian Network prediction as an additional covariate, a Mixed Effects engine modelling interactions between covariates, and an Evolutionary engine exploiting the genetic barrier to drug resistance as an additional predictor. read more.

EuResist integrated database

The EuResist Integrated DataBase (EIDB) was set up to develop the EuResist prediction system. It is available for scientific purposes upon request. The EIDB includes information about patient demographics, drug therapies, AIDS defining events, CD4 and viral load measurements, and HIV sequences. As of April 2014 it contains the following data:

Patients 66.254
Therapies 159.261
Viral Load data 754.270
CD4 counts 789.306
PR sequences 65.688
RT sequences 66.145
IN sequences 3.328
V3 sequences 2.155
GP41 sequences 560
GP120 sequences 2.228

The EIDB integrates biomedical information from the three founding national databases: ARCA (Italy), AREVIR (Germany), Karolinska Institute (Sweden). The original data set is continuously updated with new data in order to improve the accuracy of the prediction system. Following the EIDB setup, data have also been uploaded from the Laboratoire de Rétrovirologie of CRP-Santé (Luxembourg), the Rega Institute (Leuven - Belgium), the IrsiCaixa Foundation (Barcelona – Spain), the Instituto de Higiene e Medicina Tropical (Portugal) and from the DUET study (Tibotec). read more.

Contribution to the database

The service is and will remain free of charge. Like any data-driven engine, availability of new data is crucial for updating and improving the system. You can contribute genotype-response data to the EuResist initiative under the current regulations. (database). The EuResist data set is available upon request for scientific studies related to HIV domain.

Authors

  • Abbott
    EuResist Network received a grant from Abbott
  • The EuResist project has been supported by the EC within the Sixth Framework Programme
  • Pfizer
    EuResist Network received a grant from Pfizer