Predicting the response to combination antiretroviral therapy: retrospective validation of geno2pheno-THEO on a large clinical database.
BACKGROUND
Expert-based genotypic interpretation systems are standard methods for guiding treatment selection for patients infected with human immunodeficiency virus type 1. We previously introduced the software pipeline geno2pheno-THEO (g2p-THEO), which on the basis of viral sequence predicts the response to treatment with a combination of antiretroviral compounds by applying methods from statistical learning and the estimated potential of the virus to escape from drug pressure.


METHODS
We retrospectively validated the statistical model used by g2p-THEO in approximately 7600 independent treatment-sequence pairs extracted from the EuResist integrated database, ranging from 1990 to 2007. Results were compared with the 3 most widely used expert-based interpretation systems: Stanford HIVdb, ANRS, and Rega.


RESULTS
The difference in receiver operating characteristic curves between g2p-THEO and expert-based approaches was significant (P < .001; paired Wilcoxon test). Indeed, at 80% specificity, g2p-THEO found 16.2%-19.8% more successful regimens than did the expert-based approaches. The increased performance of g2p-THEO was confirmed in a 2001-2007 data set from which most obsolete therapies had been removed.


CONCLUSIONS
Finding drug combinations that increase the chances of therapeutic success is the main reason for using decision support systems. The present analysis of a large data set derived from clinical practice demonstrates that g2p-THEO solves this task significantly better than state-of-the-art expert-based systems. The tool is available at http://www.geno2pheno.org.
Altmann
André
A
Max Planck Institute for Informatics, Saarbrücken, University of Cologne, Cologne, Germany. altmann@mpi-inf.mpg.de
Däumer
Martin
M
Beerenwinkel
Niko
N
Peres
Yardena
Y
Schülter
Eugen
E
Büch
Joachim
J
Rhee
Soo-Yon
SY
Sönnerborg
Anders
A
Fessel
W Jeffrey
WJ
Shafer
Robert W
RW
Zazzi
Maurizio
M
Kaiser
Rolf
R
Lengauer
Thomas
T
D019380:Anti-HIV Agents / Q000008:administration & dosage* / Q000494:pharmacology*; D020000:Decision Support Systems, Clinical; D004359:Drug Therapy, Combination; D020022:Genetic Predisposition to Disease; D005838:Genotype; D015658:HIV Infections / Q000188:drug therapy*; D015497:HIV-1 / Q000235:genetics*; D006801:Humans; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012984:Software
D019380:Anti-HIV Agents