Predicting Response to Antiretroviral Treatments in HIV Patients - the EuResist Project

Bidgood, Penelope, Denholm-Price, James, Fielder, Mark, Petróczi, Andrea and Thompson, Richard (2007) Predicting Response to Antiretroviral Treatments in HIV Patients - the EuResist Project. In: Statistics in Public Policy-Making: Hope vs. Reality; 16 -20 Jul 2007, York, U.K..

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Abstract

The EuResist project, funded under EC FP 6, aims to develop a European integrated system for clinical management of antiretroviral drug resistance. It will provide clinicians with a prediction of response to antiretroviral treatment in HIV patients, thus helping them to choose the best drug combinations for any given HIV genetic variant. To this end a large integrated database has been formed from merging data from three European countries (located in Northern, Central and Southern Europe) with different immigration flows and features of the HIV epidemic. These individual datasets include information from more than 17,000 patients and their treatments since the 1980’s; patient characteristics, virus genotype and details of the treatment regime are recorded. The variety of data allows development of a predictive model that is both robust and reliable. Statistical analysis is used to identify significant factors in predicting treatment “success” or “failure”, which themselves can be defined in a variety of ways. The longitudinal and dynamic nature of the data allows comparison between different treatment regimes and provides a unique opportunity to identify a proxy measure for estimating patients’ adherence. This paper will report some of the initial statistical findings based on the EuResist integrated database, currently the largest on HIV patients in the world.

Item Type: Conference or Workshop Item (Poster)
Event Title: Statistics in Public Policy-Making: Hope vs. Reality
Research Area: Allied health professions and studies
Faculty, School or Research Centre: Faculty of Science (until 2011)
Faculty of Science (until 2011) > School of Life Sciences
Depositing User: Automatic Import Agent
Date Deposited: 18 Jun 2010 11:28
Last Modified: 12 Oct 2012 09:54
URI: http://eprints.kingston.ac.uk/id/eprint/8445

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