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动态逻辑回归模型和人群归因分数研究药物依从性、漏诊与死亡率的关系:一项抗逆转录病毒治疗第一年存活的 HIV 感染成年人的研究。

Dynamic logistic regression model and population attributable fraction to investigate the association between adherence, missed visits and mortality: a study of HIV-infected adults surviving the first year of ART.

出版信息

BMC Infect Dis. 2013 Aug 27;13:395. doi: 10.1186/1471-2334-13-395.

DOI:10.1186/1471-2334-13-395
PMID:24060199
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3847061/
Abstract

BACKGROUND

Adherence is one of the most important determinants of viral suppression and drug resistance in HIV-infected people receiving antiretroviral therapy (ART).

METHODS

We examined the association between long-term mortality and poor adherence to ART in DART trial participants in Uganda and Zimbabwe randomly assigned to receive laboratory and clinical monitoring (LCM), or clinically driven monitoring (CDM). Since over 50% of all deaths in the DART trial occurred during the first year on ART, we focussed on participants continuing ART for 12 months to investigate the implications of longer-term adherence to treatment on mortality. Participants' ART adherence was assessed by pill counts and structured questionnaires at 4-weekly clinic visits. We studied the effect of recent adherence history on the risk of death at the individual level (odds ratios from dynamic logistic regression model), and on mortality at the population level (population attributable fraction based on this model). Analyses were conducted separately for both randomization groups, adjusted for relevant confounding factors. Adherence behaviour was also confounded by a partial factorial randomization comparing structured treatment interruptions (STI) with continuous ART (CT).

RESULTS

In the CDM arm a significant association was found between poor adherence to ART in the previous 3-9 months with increased mortality risk. In the LCM arm the association was not significant. The odds ratios for mortality in participants with poor adherence against those with optimal adherence was 1.30 (95% CI 0.78,2.10) in the LCM arm and 2.18 (1.47,3.22) in the CDM arm. The estimated proportions of deaths that could have been avoided with optimal adherence (population attributable fraction) in the LCM and CDM groups during the 5 years follow-up period were 16.0% (95% CI 0.7%,31.6%) and 33.1% (20.5%,44.8%), correspondingly.

CONCLUSIONS

Recurrent poor adherence determined even through simple measures is associated with high mortality both at individual level as well as at the ART programme level. The number of lives saved through effective interventions to improve adherence could be considerable particularly for individuals monitored without using CD4 cell counts. The findings have important implications for clinical practice and for developing interventions to enhance adherence.

摘要

背景

在接受抗逆转录病毒疗法(ART)的艾滋病毒感染者中,依从性是病毒抑制和耐药性的最重要决定因素之一。

方法

我们研究了在乌干达和津巴布韦接受实验室和临床监测(LCM)或临床驱动监测(CDM)随机分组的 DART 试验参与者中,长期死亡率与 ART 依从性差之间的关联。由于 DART 试验中超过 50%的死亡发生在 ART 的第一年,因此我们专注于继续接受 ART 治疗 12 个月的参与者,以研究更长时间的治疗依从性对死亡率的影响。参与者的 ART 依从性通过 4 周一次的诊所就诊时的药丸计数和结构化问卷进行评估。我们研究了个体水平上最近的依从性历史对死亡风险的影响(来自动态逻辑回归模型的比值比),以及人群水平上的死亡率(基于该模型的人群归因分数)。对两个随机分组分别进行了分析,并针对相关混杂因素进行了调整。在 CDM 臂中,发现在过去 3-9 个月内 ART 依从性差与死亡率风险增加之间存在显著关联。在 LCM 臂中,关联不显著。与最佳依从性相比,依从性差的参与者的死亡率比值比为 1.30(95%CI 0.78,2.10)在 LCM 臂,和 2.18(1.47,3.22)在 CDM 臂。在 LCM 和 CDM 组的 5 年随访期间,最佳依从性(人群归因分数)可避免的死亡比例估计分别为 16.0%(95%CI 0.7%,31.6%)和 33.1%(20.5%,44.8%)。

结论

即使通过简单措施确定的反复依从性差与个体水平和 ART 项目水平的高死亡率相关。通过有效的干预措施提高依从性可以挽救大量生命,特别是对于不使用 CD4 细胞计数进行监测的个体。这些发现对临床实践和开发提高依从性的干预措施具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5e/3847061/f54292488bb8/1471-2334-13-395-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5e/3847061/76b0515673bd/1471-2334-13-395-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5e/3847061/60be0a2cfd94/1471-2334-13-395-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5e/3847061/537812a58c34/1471-2334-13-395-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5e/3847061/f54292488bb8/1471-2334-13-395-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5e/3847061/76b0515673bd/1471-2334-13-395-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5e/3847061/60be0a2cfd94/1471-2334-13-395-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5e/3847061/537812a58c34/1471-2334-13-395-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5e/3847061/f54292488bb8/1471-2334-13-395-4.jpg

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