Viral suppression following switch to second-line antiretroviral therapy: associations with nucleoside reverse transcriptase inhibitor resistance and subtherapeutic drug concentrations prior to switch.

BACKGROUND: High rates of second-line antiretroviral treatment (ART) failure are reported. The association with resistance and nonadherence on switching to second-line ART requires clarification. METHODS: Using prospectively collected data from patients in South Africa, we constructed a cohort of patients switched to second-line ART (1 January 2003 through 31 December 2008). Genotyping and drug concentrations (lamivudine, nevirapine, and efavirenz) were measured on stored samples preswitch. Their association with viral load (VL) <400 copies/mL by 15 months was assessed using modified Poisson regression. RESULTS: One hundred twenty-two of 417 patients (49% male; median age, 36 years) had genotyping (n = 115) and/or drug concentrations (n = 80) measured. Median CD4 count and VL at switch were 177 cells/µL (interquartile range [IQR], 77-263) and 4.3 log10 copies/mL (IQR, 3.8-4.7), respectively. Fifty-five percent (n = 44/80) had subtherapeutic drug concentrations preswitch. More patients with therapeutic vs subtherapeutic ART had resistance (n = 73): no major mutations (3% vs 51%), nonnucleoside reverse transcriptase inhibitor (94% vs 44%), M184V/I (94% vs 26%), and ≥ 1 thymidine analogue mutations (47% vs 18%), all P = .01; and nucleoside reverse transcriptase inhibitor (NRTI) cross-resistance mutations (26% vs 13%, P = .23). Following switch, 68% (n = 83/122) achieved VL <400 copies/mL. Absence of NRTI mutations and subtherapeutic ART preswitch were associated with failure to achieve VL <400 copies/mL. CONCLUSIONS: Nonadherence, suggested by subtherapeutic ART with/without major resistance mutations, significantly contributed to failure when switching regimen. Unresolved nonadherence, not NRTI resistance, drives early second-line failure

Surveillance of Transmitted HIV-1 Drug Resistance in Gauteng and KwaZulu-Natal Provinces, South Africa, 2005-2009

Surveillance of human immunodeficiency virus type 1 transmitted drug resistance (TDR) was conducted among pregnant women in South Africa over a 5-year period after the initiation of a large national antiretroviral treatment program. Analysis of TDR data from 9 surveys conducted between 2005 and 2009 in 2 provinces of South Africa suggests that while TDR remains low (<5%) in Gauteng Province, it may be increasing in KwaZulu-Natal, with the most recent survey showing moderate (5%-15%) levels of resistance to the nonnucleoside reverse transcriptase inhibitor drug clas

The value of information resources in sustaining SMME Projects in Limpopo Province

Journal article, Published in International Conference on Public Administration and Development Alternatives (IPADA), The 2nd Annual Conference on ‛‛ The Independence of African States in the Age of Globalisation”, July 26-28, 2017Information is crucial for improvement of the lives of any nation and has no substitute when it comes to the development because it has been identified as the driver of economic growth and productivity. There has been an acknowledgement from government that the previous regime government neglected the potential contribution of the SMMEs towards economic growth and job creation. South Africa continues to struggle with the sustainability of SMMEs. Most of these SMMEs are found in rural area of Limpopo and in agriculture and in health. Most of the SMME projects cover rural communities in Africa where the projects do not survive due to lack of relevant information. The information needs of SMME project owners vary. Therefore, such needs should be identified and matched with the resources. SMMEs may need information on how to run projects, the cost of project and know other project owners doing similar business. For example, those who are involved in the production or selling of goods would like to know where to products/good at a cheaper price, where to market them, and find customers for the products or goods. Project owners get information from different information centres. The majority of SMMEs have failed to grow or rather, more seriously, they have failed to survive. The failure is sometimes associated to a lack of access to information largely due to the fact that information is still not seen as an important as other natural resources by planners, developers and governments. There are SMMEs that do not consider the information as the important resource that would enable them to develop and sustain their projects. There are different types of SMMEs depending on the nature of their daily operations, the market they are in, and how they are organised and managed, agricultural farming, poultry farming, but they all need information. SMMEs need access to timely and relevant information. This paper seeks to establish the value of information resources to SMMEs. Thus the paper will assist to, identify information needs of SMMEs, improving access to information and improving provision of quality information to these owners. Lastly, the authors of this paper suggest solutions on the lack of access to relevant information questions so as to improve sustainability of the SMMEs in Limpopo Province

Computational models as predictors of HIV treatment outcomes for the Phidisa cohort in South Africa

Background: Selecting the optimal combination of HIV drugs for an individual in resourcelimited settings is challenging because of the limited availability of drugs and genotyping.Objective: The evaluation as a potential treatment support tool of computational models that predict response to therapy without a genotype, using cases from the Phidisa cohort in South Africa.Methods: Cases from Phidisa of treatment change following failure were identified that had the following data available: baseline CD4 count and viral load, details of failing and previous antiretroviral drugs, drugs in new regimen and time to follow-up. The HIV Resistance Response Database Initiative’s (RDI’s) models used these data to predict the probability of a viral load &lt; 50 copies/mL at follow-up. The models were also used to identify effective alternative combinations of three locally available drugs.Results: The models achieved accuracy (area under the receiver–operator  characteristic curve) of 0.72 when predicting response to therapy, which is less accurate than for an independent global test set (0.80) but at least comparable to that of genotyping with rules-based interpretation. The models were able to identify alternative locally available three-drug regimens that were predicted to be effective in 69% of all cases and 62% of those whose new treatment failed in the clinic.Conclusion: The predictive accuracy of the models for these South African patients together with the results of previous studies suggest that the RDI’s models have the potential to optimise treatment selection and reduce virological failure in different patient populations, without the use of a genotype

Computational models as predictors of HIV treatment outcomes for the Phidisa cohort in South Africa

Background: Selecting the optimal combination of HIV drugs for an individual in resourcelimited settings is challenging because of the limited availability of drugs and genotyping. Objective: The evaluation as a potential treatment support tool of computational models that predict response to therapy without a genotype, using cases from the Phidisa cohort in South Africa. Methods: Cases from Phidisa of treatment change following failure were identified that had the following data available: baseline CD4 count and viral load, details of failing and previous antiretroviral drugs, drugs in new regimen and time to follow-up. The HIV Resistance Response Database Initiative’s (RDI’s) models used these data to predict the probability of a viral load < 50 copies/mL at follow-up. The models were also used to identify effective alternative combinations of three locally available drugs. Results: The models achieved accuracy (area under the receiver–operator characteristic curve) of 0.72 when predicting response to therapy, which is less accurate than for an independent global test set (0.80) but at least comparable to that of genotyping with rules-based interpretation. The models were able to identify alternative locally available three-drug regimens that were predicted to be effective in 69% of all cases and 62% of those whose new treatment failed in the clinic. Conclusion: The predictive accuracy of the models for these South African patients together with the results of previous studies suggest that the RDI’s models have the potential to optimise treatment selection and reduce virological failure in different patient populations, without the use of a genotype. Keywords: HIV therapy; mathematical modelling; treatment; genotyp

Trends in Pretreatment HIV-1 Drug Resistance in Antiretroviral Therapy-naive Adults in South Africa, 2000–2016: A Pooled Sequence Analysis

Background: South Africa has the largest public antiretroviral therapy (ART) programme in the world. We assessed temporal trends in pretreatment HIV-1 drug resistance (PDR) in ART-naïve adults from South Africa. Methods: We included datasets from studies conducted between 2000 and 2016, with HIV-1 pol sequences from more than ten ART-naïve adults. We analysed sequences for the presence of 101 drug resistance mutations. We pooled sequences by sampling year and performed a sequence-level analysis using a generalized linear mixed model, including the dataset as a random effect. Findings: We identified 38 datasets, and retrieved 6880 HIV-1 pol sequences for analysis. The pooled annual prevalence of PDR remained below 5% until 2009, then increased to a peak of 11·9% (95% confidence interval (CI) 9·2-15·0) in 2015. The pooled annual prevalence of non-nucleoside reverse-transcriptase inhibitor (NNRTI) PDR remained below 5% until 2011, then increased to 10.0% (95% CI 8.4–11.8) by 2014. Between 2000 and 2016, there was a 1.18-fold (95% CI 1.13–1.23) annual increase in NNRTI PDR (p < 0.001), and a 1.10-fold (95% CI 1.05–1.16) annual increase in nucleoside reverse-transcriptase inhibitor PDR (p = 0.001). Interpretation: Increasing PDR in South Africa presents a threat to the efforts to end the HIV/AIDS epidemic. These findings support the recent decision to modify the standard first-line ART regimen, but also highlights the need for broader public health action to prevent the further emergence and transmission of drug-resistant HIV. Source of Funding: This research project was funded by the South African Medical Research Council (MRC) with funds from National Treasury under its Economic Competitiveness and Support Package. Disclaimer: The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of CDC

Cellular binding partners of the human papillomavirus E6 protein

The high-risk strains of human papillomavirus (HR-HPV) are known to be causative agents of cervical cancer and have recently also been implicated in cancers of the oropharynx. E6 is a potent oncogene of HR-HPVs, and its role in the progression to malignancy has been and continues to be explored. E6 is known to interact with and subsequently inactivate numerous cellular proteins pivotal in the mediation of apoptosis, transcription of tumor suppressor genes, maintenance of epithelial organization, and control of cell proliferation. Binding of E6 to these proteins cumulatively contributes to the oncogenic potential of HPV. This paper provides an overview of these cellular protein partners of HR-E6, the motifs known to mediate oncoprotein binding, and the agents that have the potential to interfere with E6 expression and activity and thus prevent the subsequent progression to oncogenesis

Resistance to tenofovir-based regimens during treatment failure of subtype C HIV-1 in South Africa.

BACKGROUND: Tenofovir disoproxil fumarate (TDF) is increasingly available for patients infected with subtype C HIV-1. This subtype is reported to develop the principal TDF resistance mutation in the HIV reverse transcriptase, K65R, with greater propensity than other subtypes. We sought to describe K65R development during TDF use in a cohort of patients infected with subtype C HIV. METHODS: Using a prospectively followed cohort with 6 monthly HIV RNA assays, we identified virological failure (defined as an HIV RNA > 1,000 copies/ml) during treatment that included TDF. Residual serum, stored at the time of the HIV RNA assay, was used for consensus sequencing and allele-specific PCR. We assessed prevalence of resistance at failure during TDF-containing treatment and associated factors. RESULTS: Among 1,682 patients on a TDF-containing regimen, 270 developed failure of which 40 were assessed for resistance. By sequencing, the K65R was identified in 5 (12%), major non-nucleoside reverse transcriptase inhibitor mutations in 24 (57%) and the M184V/I in 12 (28%) patients. The K65R was associated with lower HIV RNA at failure (HIV RNA 3.3 versus 4.2 log10 copies/ml) and prior stavudine exposure. An additional five patients had minority K65R populations identified by allele-specific PCR. CONCLUSIONS: These data suggest that the K65R prevalence at virological failure is moderately higher in our subtype C population than some non-subtype C HIV cohorts. However, we did not find that the K65R was highly selected in HIV-1 subtype-C-infected patients with up to 6 months of failure of a TDF-containing regimen