Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2016 Oct;71(10):2928-37.
doi: 10.1093/jac/dkw217. Epub 2016 Jun 20.

An update to the HIV-TRePS system: the development and evaluation of new global and local computational models to predict HIV treatment outcomes, with or without a genotype

Andrew D Revell  1 , Dechao Wang  2 , Robin Wood  3 , Carl Morrow  3 , Hugo Tempelman  4 , Raph L Hamers  5 , Peter Reiss  6 , Ard I van Sighem  7 , Mark Nelson  8 , Julio S G Montaner  9 , H Clifford Lane  10 , Brendan A Larder  2 ; RDI Data and Study Group
Collaborators, Affiliations

An update to the HIV-TRePS system: the development and evaluation of new global and local computational models to predict HIV treatment outcomes, with or without a genotype

Andrew D Revell et al. J Antimicrob Chemother. 2016 Oct.

Abstract

Objectives: Optimizing antiretroviral drug combination on an individual basis in resource-limited settings is challenging because of the limited availability of drugs and genotypic resistance testing. Here, we describe our latest computational models to predict treatment responses, with or without a genotype, and compare the potential utility of global and local models as a treatment tool for South Africa.

Methods: Global random forest models were trained to predict the probability of virological response to therapy following virological failure using 29 574 treatment change episodes (TCEs) without a genotype, 3179 of which were from South Africa and were used to develop local models. In addition, 15 130 TCEs including genotypes were used to develop another set of models. The 'no-genotype' models were tested with an independent global test set (n = 1700) plus a subset from South Africa (n = 222). The genotype models were tested with 750 independent cases.

Results: The global no-genotype models achieved area under the receiver-operating characteristic curve (AUC) values of 0.82 and 0.79 with the global and South African tests sets, respectively, and the South African models achieved AUCs of 0.70 and 0.79. The genotype models achieved an AUC of 0.84. The global no-genotype models identified more alternative, locally available regimens that were predicted to be effective for cases that failed their new regimen in the South African clinics than the local models. Both sets of models were significantly more accurate predictors of outcomes than genotyping with rules-based interpretation.

Conclusions: These latest global models predict treatment responses accurately even without a genotype, out-performed the local South African models and have the potential to help optimize therapy, particularly in resource-limited settings.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Schematic of data extraction, partition, model training and testing. SA, South African.
Figure 2.
Figure 2.
ROC curves for the global and local (South African) models in independent testing with global and local (South African) test data.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Günthard HF, Aberg JA, Eron JJ et al. Antiretroviral treatment of adult HIV infection: 2014 recommendations of the International Antiviral Society–USA Panel. JAMA 2014; 312: 410–25. - PubMed
    1. Writing Group, Williams I, Churchill D et al. British HIV Association guidelines for the treatment of HIV-1-positive adults with antiretroviral therapy 2012 (Updated November 2013. All changed text is cast in yellow highlight.) . HIV Medicine 2014; 15 Suppl 1: 1–85. - PubMed
    1. Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the Use of Antiretroviral Agents in HIV-1-Infected Adults and Adolescents. Department of Health and Human Services; http://aidsinfo.nih.gov/contentfiles/lvguidelines/AdultandAdolescentGL.pdf.
    1. Degruttola V, Dix L, D'Aquila R et al. The relation between baseline HIV drug resistance and response to antiretroviral therapy: re-analysis of retrospective and prospective studies using a standardized data analysis plan. Antivir Ther 2000; 5: 41–8. - PubMed
    1. South African Drug Resistance Guidelines. http://www.sahivsoc.org/upload/documents/HIVDRStrategy.pdf.

Publication types

Substances