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Determinants of viral load rebound on HIV/AIDS patients receiving antiretroviral therapy: results from South Africa

BACKGROUND: Antiretroviral therapy (ART) has become the standard of care for patients with HIV infection in South Africa and has led to the reduction in AIDS related morbidity and mortality. In developing countries, the nucleosides reverse transcriptase inhibitors (NRTIs) class are widely used becau...

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Autores principales: Shoko, Claris, Chikobvu, Delson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6047135/
https://www.ncbi.nlm.nih.gov/pubmed/30008270
http://dx.doi.org/10.1186/s12976-018-0082-0
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author Shoko, Claris
Chikobvu, Delson
author_facet Shoko, Claris
Chikobvu, Delson
author_sort Shoko, Claris
collection PubMed
description BACKGROUND: Antiretroviral therapy (ART) has become the standard of care for patients with HIV infection in South Africa and has led to the reduction in AIDS related morbidity and mortality. In developing countries, the nucleosides reverse transcriptase inhibitors (NRTIs) class are widely used because of their low production costs. However patients treated with NRTIs develop varying degree of toxicity after long-term therapy. For this study patients are administered with a triple therapy of two NRTIs and one non-nucleoside reverse transcriptase inhibitor (NNRTI). METHOD: In this study the progression of HIV in vivo is divided into some viral load states and a continuous time-homogeneous model is fitted to assess the effects of covariates namely gender, age, CD4 baseline, viral load baseline, lactic acidosis, peripheral neuropathy, non-adherence and resistance to treatment on transition intensities between the states. Effects of different drug combinations on transition intensities are also assessed. RESULTS: The results show no gender differences on transition intensities. The likelihood ratio test shows that the continuous time Markov model for the effects of the covariates including combination give a significantly better fit to the observed data. From almost all states, rates of viral suppression were higher than rates of viral rebound except for patients in state 2 (viral load between 50 and 10,000 copies/mL) where rates of viral rebound to state 3 (viral load between 10,000 and 100,000 copies/mL) were higher than rates of viral suppression to undetectable levels. For this transition, confidence intervals were very small. This was quite notable for patients who were administered with AZT-3TC-LPV/r and FTC-TDF-EFV. Although patients on d4T-3TC-EFV also had higher rates of viral rebound from state 2 than suppression, the difference was not significant. CONCLUSION: From these findings, we can conclude that administering of any HIV drug regimen is better when based on the viral load level of an HIV+ patient. Before initiation of treatment, patients should be well equipped on how antiretroviral drugs operate including possibilities of toxicity in order to reduce chances of non-adherence to treatment. There should also be a good relationship between patient and health-care-giver to ensure proper adherence to treatment. Uptake of therapy by young patients should be closely monitored by adopting pill counting every time they come for review.
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spelling pubmed-60471352018-07-19 Determinants of viral load rebound on HIV/AIDS patients receiving antiretroviral therapy: results from South Africa Shoko, Claris Chikobvu, Delson Theor Biol Med Model Research BACKGROUND: Antiretroviral therapy (ART) has become the standard of care for patients with HIV infection in South Africa and has led to the reduction in AIDS related morbidity and mortality. In developing countries, the nucleosides reverse transcriptase inhibitors (NRTIs) class are widely used because of their low production costs. However patients treated with NRTIs develop varying degree of toxicity after long-term therapy. For this study patients are administered with a triple therapy of two NRTIs and one non-nucleoside reverse transcriptase inhibitor (NNRTI). METHOD: In this study the progression of HIV in vivo is divided into some viral load states and a continuous time-homogeneous model is fitted to assess the effects of covariates namely gender, age, CD4 baseline, viral load baseline, lactic acidosis, peripheral neuropathy, non-adherence and resistance to treatment on transition intensities between the states. Effects of different drug combinations on transition intensities are also assessed. RESULTS: The results show no gender differences on transition intensities. The likelihood ratio test shows that the continuous time Markov model for the effects of the covariates including combination give a significantly better fit to the observed data. From almost all states, rates of viral suppression were higher than rates of viral rebound except for patients in state 2 (viral load between 50 and 10,000 copies/mL) where rates of viral rebound to state 3 (viral load between 10,000 and 100,000 copies/mL) were higher than rates of viral suppression to undetectable levels. For this transition, confidence intervals were very small. This was quite notable for patients who were administered with AZT-3TC-LPV/r and FTC-TDF-EFV. Although patients on d4T-3TC-EFV also had higher rates of viral rebound from state 2 than suppression, the difference was not significant. CONCLUSION: From these findings, we can conclude that administering of any HIV drug regimen is better when based on the viral load level of an HIV+ patient. Before initiation of treatment, patients should be well equipped on how antiretroviral drugs operate including possibilities of toxicity in order to reduce chances of non-adherence to treatment. There should also be a good relationship between patient and health-care-giver to ensure proper adherence to treatment. Uptake of therapy by young patients should be closely monitored by adopting pill counting every time they come for review. BioMed Central 2018-07-16 /pmc/articles/PMC6047135/ /pubmed/30008270 http://dx.doi.org/10.1186/s12976-018-0082-0 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Shoko, Claris
Chikobvu, Delson
Determinants of viral load rebound on HIV/AIDS patients receiving antiretroviral therapy: results from South Africa
title Determinants of viral load rebound on HIV/AIDS patients receiving antiretroviral therapy: results from South Africa
title_full Determinants of viral load rebound on HIV/AIDS patients receiving antiretroviral therapy: results from South Africa
title_fullStr Determinants of viral load rebound on HIV/AIDS patients receiving antiretroviral therapy: results from South Africa
title_full_unstemmed Determinants of viral load rebound on HIV/AIDS patients receiving antiretroviral therapy: results from South Africa
title_short Determinants of viral load rebound on HIV/AIDS patients receiving antiretroviral therapy: results from South Africa
title_sort determinants of viral load rebound on hiv/aids patients receiving antiretroviral therapy: results from south africa
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6047135/
https://www.ncbi.nlm.nih.gov/pubmed/30008270
http://dx.doi.org/10.1186/s12976-018-0082-0
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