Only slight impact of predicted replicative capacity for therapy response prediction.

<h4>Background</h4>Replication capacity (RC) of specific HIV isolates is occasionally blamed for unexpected treatment responses. However, the role of viral RC in response to antiretroviral therapy is not yet fully understood.<h4>Materials and methods</h4>We developed a method...

Full description

Bibliographic Details
Main Authors: Hendrik Weisser, André Altmann, Saleta Sierra, Francesca Incardona, Daniel Struck, Anders Sönnerborg, Rolf Kaiser, Maurizio Zazzi, Monika Tschochner, Hauke Walter, Thomas Lengauer
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2010-02-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20140263/pdf/?tool=EBI
id doaj-afa29afc63414378805fd1bcf93a9165
record_format Article
spelling doaj-afa29afc63414378805fd1bcf93a91652021-03-04T02:33:04ZengPublic Library of Science (PLoS)PLoS ONE1932-62032010-02-0152e904410.1371/journal.pone.0009044Only slight impact of predicted replicative capacity for therapy response prediction.Hendrik WeisserAndré AltmannSaleta SierraFrancesca IncardonaDaniel StruckAnders SönnerborgRolf KaiserMaurizio ZazziMonika TschochnerHauke WalterThomas Lengauer<h4>Background</h4>Replication capacity (RC) of specific HIV isolates is occasionally blamed for unexpected treatment responses. However, the role of viral RC in response to antiretroviral therapy is not yet fully understood.<h4>Materials and methods</h4>We developed a method for predicting RC from genotype using support vector machines (SVMs) trained on about 300 genotype-RC pairs. Next, we studied the impact of predicted viral RC (pRC) on the change of viral load (VL) and CD4(+) T-cell count (CD4) during the course of therapy on about 3,000 treatment change episodes (TCEs) extracted from the EuResist integrated database. Specifically, linear regression models using either treatment activity scores (TAS), the drug combination, or pRC or any combination of these covariates were trained to predict change in VL and CD4, respectively.<h4>Results</h4>The SVM models achieved a Spearman correlation (rho) of 0.54 between measured RC and pRC. The prediction of change in VL (CD4) was best at 180 (360) days, reaching a correlation of rho = 0.45 (rho = 0.27). In general, pRC was inversely correlated to drug resistance at treatment start (on average rho = -0.38). Inclusion of pRC in the linear regression models significantly improved prediction of virological response to treatment based either on the drug combination or on the TAS (t-test; p-values range from 0.0247 to 4 10(-6)) but not for the model using both TAS and drug combination. For predicting the change in CD4 the improvement derived from inclusion of pRC was not significant.<h4>Conclusion</h4>Viral RC could be predicted from genotype with moderate accuracy and could slightly improve prediction of virological treatment response. However, the observed improvement could simply be a consequence of the significant correlation between pRC and drug resistance.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20140263/pdf/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Hendrik Weisser
André Altmann
Saleta Sierra
Francesca Incardona
Daniel Struck
Anders Sönnerborg
Rolf Kaiser
Maurizio Zazzi
Monika Tschochner
Hauke Walter
Thomas Lengauer
spellingShingle Hendrik Weisser
André Altmann
Saleta Sierra
Francesca Incardona
Daniel Struck
Anders Sönnerborg
Rolf Kaiser
Maurizio Zazzi
Monika Tschochner
Hauke Walter
Thomas Lengauer
Only slight impact of predicted replicative capacity for therapy response prediction.
PLoS ONE
author_facet Hendrik Weisser
André Altmann
Saleta Sierra
Francesca Incardona
Daniel Struck
Anders Sönnerborg
Rolf Kaiser
Maurizio Zazzi
Monika Tschochner
Hauke Walter
Thomas Lengauer
author_sort Hendrik Weisser
title Only slight impact of predicted replicative capacity for therapy response prediction.
title_short Only slight impact of predicted replicative capacity for therapy response prediction.
title_full Only slight impact of predicted replicative capacity for therapy response prediction.
title_fullStr Only slight impact of predicted replicative capacity for therapy response prediction.
title_full_unstemmed Only slight impact of predicted replicative capacity for therapy response prediction.
title_sort only slight impact of predicted replicative capacity for therapy response prediction.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2010-02-01
description <h4>Background</h4>Replication capacity (RC) of specific HIV isolates is occasionally blamed for unexpected treatment responses. However, the role of viral RC in response to antiretroviral therapy is not yet fully understood.<h4>Materials and methods</h4>We developed a method for predicting RC from genotype using support vector machines (SVMs) trained on about 300 genotype-RC pairs. Next, we studied the impact of predicted viral RC (pRC) on the change of viral load (VL) and CD4(+) T-cell count (CD4) during the course of therapy on about 3,000 treatment change episodes (TCEs) extracted from the EuResist integrated database. Specifically, linear regression models using either treatment activity scores (TAS), the drug combination, or pRC or any combination of these covariates were trained to predict change in VL and CD4, respectively.<h4>Results</h4>The SVM models achieved a Spearman correlation (rho) of 0.54 between measured RC and pRC. The prediction of change in VL (CD4) was best at 180 (360) days, reaching a correlation of rho = 0.45 (rho = 0.27). In general, pRC was inversely correlated to drug resistance at treatment start (on average rho = -0.38). Inclusion of pRC in the linear regression models significantly improved prediction of virological response to treatment based either on the drug combination or on the TAS (t-test; p-values range from 0.0247 to 4 10(-6)) but not for the model using both TAS and drug combination. For predicting the change in CD4 the improvement derived from inclusion of pRC was not significant.<h4>Conclusion</h4>Viral RC could be predicted from genotype with moderate accuracy and could slightly improve prediction of virological treatment response. However, the observed improvement could simply be a consequence of the significant correlation between pRC and drug resistance.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20140263/pdf/?tool=EBI
work_keys_str_mv AT hendrikweisser onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT andrealtmann onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT saletasierra onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT francescaincardona onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT danielstruck onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT anderssonnerborg onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT rolfkaiser onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT mauriziozazzi onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT monikatschochner onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT haukewalter onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
AT thomaslengauer onlyslightimpactofpredictedreplicativecapacityfortherapyresponseprediction
_version_ 1714808561656135680