Long-Term Persistence of Primary Genotypic Resistance After HIV-1 Seroconversion

Pao, David; Andrady, Ushan; Clarke, J; Dean, Gillian; Drake, Susan M.; Fisher, Martin; Green, Tanya; Kumar, Siva; Murphy, Maurice; Tang, Alan; Taylor, Stephen; White, David; Underhill, G S; Pillay, Deenan; Cane, Patricia A.

doi:10.1097/00126334-200412150-00006

Cited by 105 publications

(90 citation statements)

References 20 publications

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“…31 The lack of time trends in pretherapy resistance prevalence, however, contrasted with reports that TDR is on the rise globally, 3,29,30,32,33 with the most extreme being East Africa experiencing a 29% increase/year, 34 but could be limited by our small number of TDR cases leading to a lack of statistical power, or differences in antiretroviral rollout staging compared to previous reports. These results were also limited by the cohort's heterogeneity in disease progression status, 32 the reversion and/or persistence of selected mutations, [35][36][37][38][39][40][41] as well as the often inaccurate self-reported treatment-naive status as shown by our HPLC-MS/MS analysis and the lack of pregnancyrelated NVP usage information.…”

Section: Discussionmentioning

confidence: 96%

“…In the UARTO pilot study (Kampala/AMU), a total of 62% participants were female with a median age of 36 years (IQR [30][31][32][33][34][35][36][37][38][39][40], baseline log viral load of 5.5 (IQR 4.9-5.8), and baseline CD4 count of 60 (IQR 12-136). All AMU participants received generic fixed dose combinations of d4T/3TC/ NVP as a first regimen.…”

Section: Baseline Characteristicsmentioning

confidence: 99%

“…All AMU participants received generic fixed dose combinations of d4T/3TC/ NVP as a first regimen. In the UARTO main cohort (Mbarara/MBA), a total of 70% of participants were female with a median age of 35 years (IQR [29][30][31][32][33][34][35][36][37][38][39], baseline viral load of 5.1 log 10 HIV-RNA copies/ml (IQR 4.7-5.6), and baseline CD4 count of 131 . Initial regimens were primarily NVP based (86%) and EFV based (12%) in combination with lamivudine (3TC) and zidovudine (AZT) backbones.…”

Section: Baseline Characteristicsmentioning

confidence: 99%

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Prevalence and Virologic Consequences of Transmitted HIV-1 Drug Resistance in Uganda

Lee

Bangsberg

Muzoora

et al. 2014

AIDS Research and Human Retroviruses

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Few reports have examined the impact of HIV-1 transmitted drug resistance (TDR) in resource-limited settings where there are fewer regimen choices and limited pretherapy/posttherapy resistance testing. In this study, we examined TDR prevalence in Kampala and Mbarara, Uganda and assessed its virologic consequences after antiretroviral therapy initiation. We sequenced the HIV-1 protease/reverse transcriptase from n = 81 and n = 491 treatment-naive participants of the Uganda AIDS Rural Treatment Outcomes (UARTO) pilot study in Kampala (AMU 2002(AMU -2004 and main cohort in Mbarara (MBA 2005(MBA -2010. TDR-associated mutations were defined by the WHO 2009 surveillance mutation list. Posttreatment viral load data were available for both populations. Overall TDR prevalence was 7% (Kampala) and 3% (Mbarara) with no significant time trend. There was a slight but statistically nonsignificant trend indicating that the presence of TDR was associated with a worse treatment outcome. Virologic suppression (£ 400 copies/ml within 6 months posttherapy initiation) was achieved in 87% and 96% of participants with wildtype viruses versus 67% and 83% of participants with TDR (AMU, MBA p = 0.2 and 0.1); time to suppression (log-rank p = 0.3 and p = 0.05). Overall, 85% and 96% of study participants achieved suppression regardless of TDR status. Surprisingly, among the TDR cases, approximately half still achieved suppression; the presence of pretherapy K103N while on nevirapine and fewer active drugs in the first regimen were most often observed with failures. The majority of patients benefited from the local HIV care system even without resistance monitoring. Overall, TDR prevalence was relatively low and its presence did not always imply treatment failure.

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Section: Discussionmentioning

confidence: 96%

Section: Baseline Characteristicsmentioning

confidence: 99%

Section: Baseline Characteristicsmentioning

confidence: 99%

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Prevalence and Virologic Consequences of Transmitted HIV-1 Drug Resistance in Uganda

Lee

Bangsberg

Muzoora

et al. 2014

AIDS Research and Human Retroviruses

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“…The main experimental parameters for specifying PrEP regimens were: (i) efficacy in preventing infections with wild-type strains (range: 30-90%); (ii) relative efficacy in preventing infection with resistant strains (range: zero to half as efficient against resistant strains compared with wild-type); (iii) degree of PrEP-induced reduction of viremia during primary infection (range: no reduction to 2log 10 ); (iv) rate of emergence of resistance in infected individuals on PrEP (range: 10-99% per y); and (v) reversion rates of resistant strains (that were acquired when an individual was taking PrEP) to wild-type strains (range: 6 mo or less). We also assumed resistant strains acquired through sexual transmission could revert and that reversion would take at least 2 y, as has been observed in empirical studies (5,(36)(37)(38).…”

Section: (Materials and Methods)mentioning

confidence: 99%

HIV, transmitted drug resistance, and the paradox of preexposure prophylaxis

Supervie

Garcı́a-Lerma²,

Heneine³

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

100

129

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The administration of antiretrovirals before HIV exposure to prevent infection (i.e., preexposure prophylaxis; PrEP) is under evaluation in clinical trials. Because PrEP is based on antiretrovirals, there is considerable concern that it could substantially increase transmitted resistance, particularly in resource-rich countries. Here we use a mathematical model to predict the effect of PrEP interventions on the HIV epidemic in the men-who-have-sex-with-men community in San Francisco. The model is calibrated using Monte Carlo filtering and analyzed by constructing nonlinear response hypersurfaces. We predict PrEP interventions could substantially reduce transmission but significantly increase the proportion of new infections caused by resistant strains. Two mechanisms can cause this increase. If risk compensation occurs, the proportion increases due to increasing transmission of resistant strains and decreasing transmission of wild-type strains. If risk behavior remains stable, the increase occurs because of reduced transmission of resistant strains coupled with an even greater reduction in transmission of wild-type strains. We define this as the paradox of PrEP (i.e., resistance appears to be increasing, but is actually decreasing). We determine this paradox is likely to occur if the efficacy of PrEP regimens against wild-type strains is greater than 30% and the relative efficacy against resistant strains is greater than 0.2 but less than the efficacy against wildtype. Our modeling shows, if risk behavior increases, that it is a valid concern that PrEP could significantly increase transmitted resistance. However, if risk behavior remains stable, we find the concern is unfounded and PrEP interventions are likely to decrease transmitted resistance.mathematical model | men who have sex with men | prevention | epidemics | antiretrovirals T he administration of antiretroviral drugs (ARVs) before HIV exposure to prevent infection (i.e., preexposure prophylaxis; PrEP) is currently under evaluation in clinical trials (1). The PrEP regimens under consideration are based on tenofovir (TDF) alone or in combination with emtricitabine (FTC). Results from phase III efficacy trials are expected in 2010 and several additional trials will begin soon (SI Appendix, Table S1) (2). The results from these trials are widely anticipated because, if PrEP is shown to be safe and effective, it will become an important biomedical intervention for controlling the HIV pandemic. A phase II study of TDF-based PrEP showed daily TDF in HIV-uninfected women to be safe (3). However, because PrEP is based on ARVs, there is concern that wide-scale usage could lead to a substantial increase in transmission of ARV-resistant strains (4). Such an increase would have significant clinical repercussions [as individuals infected with these strains would be limited in their future treatment options (5)], as well as exacerbate the difficulty of controlling the pandemic. In particular, increases in resistance in high-risk communities in resource-rich countries...

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“…The rate of reversion may be substantially slower in ARV-naïve individuals with TDR compared to former PrEP users who developed ADR on PrEP [57][58][59]. Future treatment is affected because resistant viruses can remain present as minority variants, which can increase the risk of virological failure.…”

Section: Resistance Mechanism Surveyedmentioning

confidence: 99%

How Much Do We Know about Drug Resistance Due to PrEP Use? Analysis of Experts' Opinion and Its Influence on the Projected Public Health Impact

DimitrovDobromir

BoilyMarie-Claude

Hallett

2014

AIDS Research and Human Retroviruses

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Long-Term Persistence of Primary Genotypic Resistance After HIV-1 Seroconversion

Cited by 105 publications

References 20 publications

Prevalence and Virologic Consequences of Transmitted HIV-1 Drug Resistance in Uganda

Prevalence and Virologic Consequences of Transmitted HIV-1 Drug Resistance in Uganda

HIV, transmitted drug resistance, and the paradox of preexposure prophylaxis

How Much Do We Know about Drug Resistance Due to PrEP Use? Analysis of Experts' Opinion and Its Influence on the Projected Public Health Impact

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