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Prediction of Virologic Outcome of Salvage Antiretroviral Treatment by Different Systems for Interpreting Genotypic HIV Drug ResistanceDivisione di Malattie Infettive, Ospedali Riuniti, Bergamo, Italy, franc031556{at}hotmail.com, Unità di Terapia Antivirale, Ospedali Riuniti, Bergamo, Italy
Divisione di Malattie Infettive, Ospedali Riuniti, Bergamo, Italy
Laboratorio di Microbiologia e Virologia, Ospedali Riuniti, Bergamo, Italy
Divisione di Malattie Infettive, Ospedali Riuniti, Bergamo, Italy, Unità di Terapia Antivirale, Ospedali Riuniti, Bergamo, Italy
Divisione di Malattie Infettive, Ospedali Riuniti, Bergamo, Italy, Unità di Terapia Antivirale, Ospedali Riuniti, Bergamo, Italy
Divisione di Malattie Infettive, Ospedali Riuniti, Bergamo, Italy, Unità di Terapia Antivirale, Ospedali Riuniti, Bergamo, Italy
Divisione di Malattie Infettive, Ospedali Riuniti, Bergamo, Italy
Divisione di Malattie Infettive, Ospedali Riuniti, Bergamo, Italy
Divisione di Malattie Infettive, Ospedali Riuniti, Bergamo, Italy
The authors assessed the predictive capacity of 3 rule-based algorithms (Bergamo, Stanford University, Rega Institute) for HIV genotypic interpretation. A total of 1132 postgenotypic regimens in 533 patients were considered. The genotypic sensitivity score (GSS) was strongly associated (P < .0001) with the virologic outcome (1 log HIV-RNA reduction). The 3 algorithms had a highly significant prediction efficiency. The Bergamo algorithm receiver-operating characteristic curve area under the curve (AUC) for the prediction of
Key Words: resistance • mutations • prediction • expert systems • virologic response • salvage therapy
Journal of the International Association of Physicians in AIDS Care (JIAPAC), Vol. 6, No. 2,
87-93 (2007) |
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1 log HIV-RNA reduction was 0.753 (95% confidence interval, 0.725-0.781), testifying that the prediction was significantly different (P < .0001) from simple chance. The AUCs obtained by the 2 other systems were similar (0.752 Stanford; 0.741 Rega). The predictive capacity of the algorithms was not influenced by the type of antiviral drugs used. The 3 considered rule-based algorithms for the interpretation of HIV genotypic resistance yield congruent results and may effectively predict the virologic outcome of rescue therapy. Their use may help clinicians in interpreting mutational patterns and in making therapeutic choices.