Prediction of response to antiretroviral therapy by human experts and by the EuResist data-driven expert system (the EVE study)

M. Zazzi, R. Kaiser, A. Sönnerborg, D. Struck, A. Altmann, M. Prosperi, M. Rosen-Zvi, A. Petroczi, Y. Peres, E. Schülter, Ca Boucher, F. Brun-Vezinet, Pr Harrigan, L. Morris, M. Obermeier, C. F. Perno, P. Phanuphak, D. Pillay, Rw Shafer, A. M. VandammeK. van Laethem, Amj Wensing, T. Lengauer, F. Incardona

Research output: Contribution to journalArticle

Abstract

Objectives: The EuResist expert system is a novel data-driven online system for computing the probability of 8-week success for any given pair of HIV-1 genotype and combination antiretroviral therapy regimen plus optional patient information. The objective of this study was to compare the EuResist system vs. human experts (EVE) for the ability to predict response to treatment. Methods: The EuResist system was compared with 10 HIV-1 drug resistance experts for the ability to predict 8-week response to 25 treatment cases derived from the EuResist database validation data set. All current and past patient data were made available to simulate clinical practice. The experts were asked to provide a qualitative and quantitative estimate of the probability of treatment success. Results: There were 15 treatment successes and 10 treatment failures. In the classification task, the number of mislabelled cases was six for EuResist and 6-13 for the human experts [mean±standard deviation (SD) 9.1±1.9]. The accuracy of EuResist was higher than the average for the experts (0.76 vs. 0.64, respectively). The quantitative estimates computed by EuResist were significantly correlated (Pearson r=0.695, P

Original languageEnglish
Pages (from-to)211-218
Number of pages8
JournalHIV Medicine
Volume12
Issue number4
DOIs
Publication statusPublished - Apr 2011

Keywords

  • Antiretroviral therapy
  • Drug resistance
  • Genotype
  • HIV type 1
  • Prediction systems

ASJC Scopus subject areas

  • Infectious Diseases
  • Pharmacology (medical)
  • Health Policy

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    Zazzi, M., Kaiser, R., Sönnerborg, A., Struck, D., Altmann, A., Prosperi, M., Rosen-Zvi, M., Petroczi, A., Peres, Y., Schülter, E., Boucher, C., Brun-Vezinet, F., Harrigan, P., Morris, L., Obermeier, M., Perno, C. F., Phanuphak, P., Pillay, D., Shafer, R., ... Incardona, F. (2011). Prediction of response to antiretroviral therapy by human experts and by the EuResist data-driven expert system (the EVE study). HIV Medicine, 12(4), 211-218. https://doi.org/10.1111/j.1468-1293.2010.00871.x