Cingolani A, Antinori A, Rizzo MG, et al.. Usefulness of monitoring HIV drug resistance and adherence in individuals failing highly active antiretroviral therapy: a randomized study (ARGENTA)
Istituto di Clinica delle Malattie Infettive, Università Cattolica del Sacro Cuore, Largo Agostino Gemelli 8, 00168 Rome, Italy. AIDS
(Impact Factor: 5.55).
03/2002; 16(3):369-79. DOI: 10.1097/00002030-200202150-00008
To establish the influence of genotypic resistance-guided treatment decisions and patient-reported adherence on the virological and immunological responses in patients failing a potent antiretroviral regimen in a randomized, controlled trial in a tertiary care infectious diseases department.
A total of 174 patients with virological failure were randomly assigned to receive standard of care (SOC) or additional genotypic resistance information (G). Adherence was measured by a self-administered questionnaire.
Primary endpoints were the proportion with HIV-RNA < 500 copies/ml at 3 and 6 months by intention-to-treat analysis. Secondary endpoints were changes from baseline HIV-RNA levels and CD4 cell counts.
At entry, 25% had failed three or more highly active antiretroviral therapy (HAART) regimens and 41% three drug classes; there were more resistance mutations in G. In 127 evaluable questionnaires, 43% reported last missed dose during the previous week. At 3 months, 11 of 89 patients (12%) in SOC and 23 of 85 (27%) in G had HIV-RNA < 500 copies/ml (OR 2.63, 95% CI 1.12-6.26); the relative proportions were 17 and 21% at 6 months. CD4 cell changes did not differ between arms. Six month CD4 cell changes were +62 in adherent and -13 cells/microl in non-adherent patients (P < 0.01). Being assigned to G, good adherence, previous history of virological success, fewer experienced HAART regimens and lower baseline viral load were independently predictive of 3 month virological success.
The virological benefit of genotype-guided treatment decisions in heavily pre-exposed patients was short term. Patients adherence and residual treatment options influenced outcomes.
Available from: Maurizio Zazzi
- "Several prospective studies have shown that the use of genotypic resistance analysis to guide the new treatment choice for patients failing their current HAART improves virologic outcome , , , . The complex mutational patterns are however difficult to interpret, due to the many different drug resistance mutations  and the varying levels of decreased susceptibility of these mutations to different drugs. "
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ABSTRACT: 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.
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 1.92+/-1.17, compared to Rega and ANRS, with 2.22+/-1.09 and 2.23+/-1.05, 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.
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.
PLoS ONE 07/2010; 5(7):e11505. DOI:10.1371/journal.pone.0011505 · 3.23 Impact Factor
Available from: PubMed Central
- "Prospective data on resistance in patients with VF supports the concept that the virologic responses to therapy are better when the results of resistance testing are available compared to the responses observed when changes in therapy are guided only by clinical judgment only (3, 4). Various aspects of genotypic resistance and clinical application have been evaluated (5-9). However, some regional factors can affect the selection of treatment, such as the availability of specific antiretroviral drugs especially in heavily treatment-experienced patients. "
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ABSTRACT: Resistance assays are useful in guiding decisions for patients experiencing virologic failure (VF) during highly-active antiretroviral therapy (HAART). We investigated antiretroviral resistance mutations in 41 Korean human immunodeficiency virus type 1 (HIV-1) infected patients with VF and observed immunologic/virologic response 6 months after HAART regimen change. Mean HAART duration prior to resistance assay was 45.3+/-27.5 months and commonly prescribed HAART regimens were zidovudine/lamivudine/nelfinavir (22.0%) and zidovudine/lamivudine/efavirenz (19.5%). Forty patients (97.6%) revealed intermediate to high-level resistance to equal or more than 2 antiretroviral drugs among prescribed HAART regimen. M184V/I mutation was observed in 36 patients (87.7%) followed by T215Y/F (41.5%) and M46I/L (34%). Six months after resistance assay and HAART regimen change, median CD4+ T cell count increased from 168 cells/microL (interquartile range [IQR], 62-253) to 276 cells/microL (IQR, 153-381) and log viral load decreased from 4.65 copies/mL (IQR, 4.18-5.00) to 1.91 copies/mL (IQR, 1.10-3.60) (P<0.001 for both values). The number of patients who accomplished viral load <400 copies/mL was 26 (63.4%) at 6 months follow-up. In conclusion, many Korean HIV-1 infected patients with VF are harboring strains with multiple resistance mutations and immunologic/virologic parameters are improved significantly after genotypic resistance assay and HAART regimen change.
Journal of Korean medical science 12/2009; 24(6):1031-7. DOI:10.3346/jkms.2009.24.6.1031 · 1.27 Impact Factor
Available from: Jurgen Vercauteren
- "Taking into account antiviral drug resistance, when choosing a therapy, is included in international guidelines (Vandamme et al., 2004; Yeni et al., 2004). Although both resistance phenotyping and genotyping after treatment failure have proven to be predictive for the next therapy response (Cingolani et al., 2002; Cohen et al., 2002; Mazzotta et al., 2003; Meynard et al., 2002; Perez-Elias et al., 2003; Tural et al., 2002; Wegner et al., 2004), genotyping is the preferred test for the routine follow-up of patients because of its faster turn-around time, the less complicated technique, and its lower cost (300–500D versus 800–1000D ). So far, no controlled prospective clinical studies have shown the advantage of using resistance testing in untreated patients although many retrospective studies support resistance testing also in drug naives (Little et al., 2002; Novak et al., 2005) such that guidelines also include resistance testing in particular circumstances for the first regimen. "
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ABSTRACT: Drug resistance testing has proven its use to guide treatment decisions in HIV-1 infected patients. Genotyping is the preferred technique for clinical drug resistance testing. Many factors complicate the interpretation of mutations towards therapy response, such that an interpretation system is necessary to help the clinical virologist. No consensus interpretation exists to date and experts often have quite different opinions. As a result, several algorithms for the interpretation of HIV-1 genotypic drug resistance information have been designed. Clinical evaluation of their genotypic interpretation is not always straightforward. We describe a few publicly available systems and their clinical evaluation. We also stress that in addition to drug resistance, for effective management of HIV infection the clinician needs to take into account all potential causes of treatment failure. Successful therapy heavily relies on the expertise of the clinician.
Antiviral Research 10/2006; 71(2-3):335-42. DOI:10.1016/j.antiviral.2006.05.003 · 3.94 Impact Factor
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