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, Dechao Wang, Robin Wood, Carl Morrow, Hugo Tempelman, Raph L Hamers, Peter Reiss, Ard I van Sighem, Mark Nelson, Julio S G Montaner, H Clifford Lane, Brendan A Larder, RDI Data and Study Group, Peter Reiss, Ard van Sighem, Julio Montaner, Richard Harrigan, Tobias Rinke de Wit, Raph Hamers, Kim Sigaloff, Brian Agan, Vincent Marconi, Scott Wegner, Wataru Sugiura, Maurizio Zazzi, Rolf Kaiser, Eugen Schuelter, Adrian Streinu-Cercel, Gerardo Alvarez-Uria, Jose Gatell, Elisa Lazzari, Brian Gazzard, Mark Nelson, Anton Pozniak, Sundhiya Mandalia, Daniel Webster, Colette Smith, Lidia Ruiz, Bonaventura Clotet, Schlomo Staszewski, Carlo Torti, Cliff Lane, Julie Metcalf, Maria-Jesus Perez-Elias, Stefano Vella, Gabrielle Dettorre, Andrew Carr, Richard Norris, Karl Hesse, Emanuel Vlahakis, Hugo Tempelman, Roos Barth, Carl Morrow, Robin Wood, Chris Hoffmann, Luminita Ene, Gordana Dragovic, Ricardo Diaz, Cecilia Sucupira, Omar Sued, Carina Cesar, Juan Sierra Madero, Sean Emery, David Cooper, Carlo Torti, John Baxter, Laura Monno, Carlo Torti, Jose Gatell, Bonventura Clotet, Gaston Picchio, Marie-Pierre deBethune, Maria-Jesus Perez-Elias, Sean Emery, Paul Khabo, Lotty Ledwaba, Andrew D Revell, Dechao Wang, Robin Wood, Carl Morrow, Hugo Tempelman, Raph L Hamers, Peter Reiss, Ard I van Sighem, Mark Nelson, Julio S G Montaner, H Clifford Lane, Brendan A Larder, RDI Data and Study Group, Peter Reiss, Ard van Sighem, Julio Montaner, Richard Harrigan, Tobias Rinke de Wit, Raph Hamers, Kim Sigaloff, Brian Agan, Vincent Marconi, Scott Wegner, Wataru Sugiura, Maurizio Zazzi, Rolf Kaiser, Eugen Schuelter, Adrian Streinu-Cercel, Gerardo Alvarez-Uria, Jose Gatell, Elisa Lazzari, Brian Gazzard, Mark Nelson, Anton Pozniak, Sundhiya Mandalia, Daniel Webster, Colette Smith, Lidia Ruiz, Bonaventura Clotet, Schlomo Staszewski, Carlo Torti, Cliff Lane, Julie Metcalf, Maria-Jesus Perez-Elias, Stefano Vella, Gabrielle Dettorre, Andrew Carr, Richard Norris, Karl Hesse, Emanuel Vlahakis, Hugo Tempelman, Roos Barth, Carl Morrow, Robin Wood, Chris Hoffmann, Luminita Ene, Gordana Dragovic, Ricardo Diaz, Cecilia Sucupira, Omar Sued, Carina Cesar, Juan Sierra Madero, Sean Emery, David Cooper, Carlo Torti, John Baxter, Laura Monno, Carlo Torti, Jose Gatell, Bonventura Clotet, Gaston Picchio, Marie-Pierre deBethune, Maria-Jesus Perez-Elias, Sean Emery, Paul Khabo, Lotty Ledwaba
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.
© The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Source: PubMed