艾滋病毒/艾滋病患者接受抗逆转录病毒治疗时病毒载量反弹的决定因素:来自南非的结果

Q1 Mathematics
Claris Shoko, Delson Chikobvu
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引用次数: 7

摘要

背景:抗逆转录病毒治疗(ART)已成为南非艾滋病毒感染者的标准治疗方法,并导致艾滋病相关发病率和死亡率的降低。在发展中国家,核苷类逆转录酶抑制剂(NRTIs)因其生产成本低而被广泛使用。然而,接受NRTIs治疗的患者在长期治疗后出现不同程度的毒性。在这项研究中,患者接受两种nrti和一种非核苷逆转录酶抑制剂(NNRTI)的三联治疗。方法:本研究将HIV在体内的进展分为若干病毒载量状态,并拟合一个连续时间均质模型,以评估协变量(性别、年龄、CD4基线、病毒载量基线、乳酸性酸中毒、周围神经病变、不依从性和治疗耐药)对状态间过渡强度的影响。还评估了不同药物组合对过渡强度的影响。结果:研究结果显示,性别在转移强度上没有差异。似然比检验表明,包含组合在内的协变量影响的连续时间马尔可夫模型与观测数据的拟合效果明显较好。在几乎所有的状态中,病毒抑制率都高于病毒反弹率,除了状态2(病毒载量在50到10,000拷贝/mL之间)的患者,病毒反弹到状态3(病毒载量在10,000到100,000拷贝/mL之间)的率高于病毒抑制到无法检测到的水平。对于这个转换,置信区间非常小。这在给予AZT-3TC-LPV/r和FTC-TDF-EFV的患者中非常明显。虽然接受d4T-3TC-EFV治疗的患者从状态2的病毒反弹率也高于抑制治疗的患者,但差异并不显著。结论:根据这些发现,我们可以得出结论,根据HIV阳性患者的病毒载量水平,使用任何HIV药物方案都是更好的。在开始治疗之前,患者应充分了解抗逆转录病毒药物的作用方式,包括毒性的可能性,以减少不坚持治疗的机会。病人和保健人员之间也应该有良好的关系,以确保适当地坚持治疗。应密切监测年轻患者对治疗的吸收,每次来复查时都应采用药片计数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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

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 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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来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
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0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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