Comparison of HIV-1 genotypic resistance test interpretation systems in predicting virological outcomes over time.
Articolo
Data di Pubblicazione:
2010
Abstract:
Background: Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results.
This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford’s HIVdb) to predict
virological outcome at 12, 24, and 48 weeks.
Methodology/Principal Findings: Included were 3763 treatment-change episodes (TCEs) for which a HIV-1 genotype was
available at the time of changing treatment with at least one follow-up viral load measurement. Genotypic susceptibility
scores for the active regimens were calculated using scores defined by each interpretation system. Using logistic regression,
we determined the association between the genotypic susceptibility score and proportion of TCEs having an undetectable
viral load (,50 copies/ml) at 12 (8–16) weeks (2152 TCEs), 24 (16–32) weeks (2570 TCEs), and 48 (44–52) weeks (1083 TCEs).
The Area under the ROC curve was calculated using a 10-fold cross-validation to compare the different interpretation
systems regarding the sensitivity and specificity for predicting undetectable viral load. The mean genotypic susceptibility
score of the systems was slightly smaller for HIVdb, with 1.9261.17, compared to Rega and ANRS, with 2.2261.09 and
2.2361.05, respectively. However, similar odds ratio’s were found for the association between each-unit increase in
genotypic susceptibility score and undetectable viral load at week 12; 1.6 [95% confidence interval 1.5–1.7] for HIVdb, 1.7
[1.5–1.8] for ANRS, and 1.7 [1.9–1.6] for Rega. Odds ratio’s increased over time, but remained comparable (odds ratio’s
ranging between 1.9–2.1 at 24 weeks and 1.9–2.2 at 48 weeks). The Area under the curve of the ROC did not differ between
the systems at all time points; p = 0.60 at week 12, p = 0.71 at week 24, and p = 0.97 at week 48.
Conclusions/Significance: Three commonly used HIV drug resistance interpretation systems ANRS, Rega and HIVdb predict
virological response at 12, 24, and 48 weeks, after change of treatment to the same extent.
This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford’s HIVdb) to predict
virological outcome at 12, 24, and 48 weeks.
Methodology/Principal Findings: Included were 3763 treatment-change episodes (TCEs) for which a HIV-1 genotype was
available at the time of changing treatment with at least one follow-up viral load measurement. Genotypic susceptibility
scores for the active regimens were calculated using scores defined by each interpretation system. Using logistic regression,
we determined the association between the genotypic susceptibility score and proportion of TCEs having an undetectable
viral load (,50 copies/ml) at 12 (8–16) weeks (2152 TCEs), 24 (16–32) weeks (2570 TCEs), and 48 (44–52) weeks (1083 TCEs).
The Area under the ROC curve was calculated using a 10-fold cross-validation to compare the different interpretation
systems regarding the sensitivity and specificity for predicting undetectable viral load. The mean genotypic susceptibility
score of the systems was slightly smaller for HIVdb, with 1.9261.17, compared to Rega and ANRS, with 2.2261.09 and
2.2361.05, respectively. However, similar odds ratio’s were found for the association between each-unit increase in
genotypic susceptibility score and undetectable viral load at week 12; 1.6 [95% confidence interval 1.5–1.7] for HIVdb, 1.7
[1.5–1.8] for ANRS, and 1.7 [1.9–1.6] for Rega. Odds ratio’s increased over time, but remained comparable (odds ratio’s
ranging between 1.9–2.1 at 24 weeks and 1.9–2.2 at 48 weeks). The Area under the curve of the ROC did not differ between
the systems at all time points; p = 0.60 at week 12, p = 0.71 at week 24, and p = 0.97 at week 48.
Conclusions/Significance: Three commonly used HIV drug resistance interpretation systems ANRS, Rega and HIVdb predict
virological response at 12, 24, and 48 weeks, after change of treatment to the same extent.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Frentz, D; Boucher, Ca; Assel, M; De Luca, A; Fabbiani, M; Incardona, F; Libin, P; Manca, Nino; Müller, V; O., Nualláin B; Paredes, R; Prosperi, M; QUIROS ROLDAN, Maria Eugenia; Ruiz, L; Sloot, Pm; Torti, Carlo; Vandamme, Am; Van Laethem, K; Zazzi, M; van de Vijver, Da
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