Association of Alcohol Consumption and HIV Surrogate Markers in Participants of the Swiss HIV Cohort Study

Conen, Anna; Wang, Qing; Glass, Tracy R.; Fux, Christoph A; Thurnheer, Maria Christine; Orasch, Christina; Calmy, Alexandra; Bernasconi, Enos; Vernazza, Pietro; Weber, Rainer; Bucher, Heiner C.; Battegay, Manuel; Fehr, Jan

doi:10.1097/qai.0b013e3182a61ea9

Cited by 53 publications

(61 citation statements)

References 39 publications

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“…Actually, one of them even proposed that low alcohol consumption can be a predictor of higher CD4+ cell count in HIV-treated patients (Carrieri et al, 2014;Conen et al, 2013). This issue is far from a consensus.…”

Section: Introductionmentioning

confidence: 92%

Alcohol dependence and CD4 cell count: is there a relationship?

2014

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Alcohol and other drugs use seem to be common among people infected with HIV on antiretroviral treatment (ART). Their effects on HIV progression is still in debate. This study aimed to assess the association between alcohol and drug use and an HIV disease progression biomarker (CD4 cell count) among patients on ART. A cross-sectional study was carried out at an HIV treatment center affiliated with Medical School of the University of São Paulo, Brazil. Four hundred and thirty-eight HIV-positive patients on ART were interviewed by trained psychiatrists and psychologists using the following instruments: Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I), Alcohol Use Disorders Identification Test (AUDIT), 17-item Hamilton Rating Scale for Depression, and the Simplified Medication Adherence Questionnaire (SMAQ). In the previous month, 219 (50%) and 41 (9.3%) patients reported use of alcohol and illicit drugs, respectively. Fifty patients (12.6%) were classified as having harmful alcohol use by AUDIT. According to SCID-I, 80 patients (18.3%) were alcohol abusers, 24 (5.5%) alcohol dependents, and 21 (4.2%) had a current depressive disorder. Almost 73% (n = 319-72.8%) of the patients were adherent to ART. Alcohol dependents were nine times (p < 0.01) more likely to have CD4 cell count ≤200/mm(3), and this association was independent of ART adherence. In conclusion, alcohol dependence seems to be associated with low CD4 cell count in HIV-positive patients. Based on these data, HIV health care workers should always assess alcohol consumption in the treatment setting, and patients should be advised that alcohol dependence may be linked to low CD4.

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Section: Introductionmentioning

confidence: 92%

Alcohol dependence and CD4 cell count: is there a relationship?

2014

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“…For individuals with liver disease and/or hepatitis C co-infection drinking while taking ART can modify liver drug metabolic rates leading to risk of drug resistance (Kresina et al, 2002). However, with the exception of individuals with compromised liver function, studies suggest that the benefits of sustained adherence to ART on viral suppression and immune system functioning outweigh the negative impacts of mixing alcohol and ART (Conen, et al, 2013; Kowalski, et al, 2012)…”

mentioning

confidence: 99%

Alcohol-antiretroviral therapy interactive toxicity beliefs and daily medication adherence and alcohol use among people living with HIV

Pellowski

Kalichman

et al. 2016

AIDS Care

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Alcohol-antiretroviral therapy (ART) interactive toxicity beliefs reflect perceived adverse outcomes of mixing alcohol and ART. Previous research has shown a significant relationship between alcohol-ART interactive toxicity beliefs and ART non-adherence, over and above other correlates of non-adherence such as HIV symptoms and frequency of alcohol use. Most past studies have collected data over extended periods and have not determined if alcohol use and missed medications occur at the day-level among people holding interactive toxicity beliefs. Previous daily analyses, however, have been limited by self-reported adherence and relatively short periods of observation. To address these gaps in the literature, men and women living with HIV in Atlanta, GA were enrolled in a 45-day observational cohort study. Daily alcohol use was collected using two-way interactive text message surveys and daily adherence was collected via the Wisepill device. Fifty-seven participants completed a measure of alcohol-ART interactive toxicity beliefs and contributed 2,565 days of daily data. Participants who endorsed high levels of interactive toxicity beliefs had significantly more days when they missed doses of medication. Alcohol-antiretroviral toxicity beliefs predicted missing doses of medication on days when participants were drinking and on days when they were not drinking. Multilevel multivariate regressions showed that these toxicity beliefs predicted daily missed doses of medication over and above quantity of alcohol consumed, depression and general medication concerns. This study replicates and extends previous literature and indicates the necessity of addressing alcohol-ART toxicity beliefs within adherence interventions.

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“…For example, recent systematic reviews on the association of alcohol and cardiovascular disease outcomes in PLWH [10], and the general population [11] found that nearly every study on the topic relied on an alcohol measurement that was obtained at a single time-point, with most studies using dichotomous categories of “drinkers” and “non-drinkers”. Similar limitations are noted in a recent review of the relationship between alcohol consumption and colorectal cancer in the general population [12], and the relationships between alcohol consumption and HIV-related outcomes such as time to ART initiation and survival [13], and rate of CD4 decline over time [8]. …”

Section: Key Issues In Analytic Strategymentioning

confidence: 64%

“…Because alcohol consumption varies over time, measurement of this exposure is complex. Alcohol consumption is highly prevalent among PLWH [8] and has been associated with biological and behavioral influences on health outcomes related to HIV/AIDS [9]. …”

Section: Introductionmentioning

confidence: 99%

Analytic strategies to evaluate the association of time-varying exposures to HIV-related outcomes: Alcohol consumption as an example

Cook

Kelso²,

Brumback³

et al. 2016

CHR

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Background As persons with HIV are living longer, there is a growing need to investigate factors associated with chronic disease, rate of disease progression and survivorship. Many risk factors for this high-risk population change over time, such as participation in treatment, alcohol consumption and drug abuse. Longitudinal datasets are increasingly available, particularly clinical data that contain multiple observations of health exposures and outcomes over time. Several analytic options are available for assessment of longitudinal data; however, it can be challenging to choose the appropriate analytic method for specific combinations of research questions and types of data. The purpose of this review is to help researchers choose the appropriate methods to analyze longitudinal data, using alcohol consumption as an example of a time-varying exposure variable. When selecting the optimal analytic method, one must consider aspects of exposure (e.g. timing, pattern, and amount) and outcome (fixed or time-varying), while also addressing minimizing bias. In this article, we will describe several analytic approaches for longitudinal data, including developmental trajectory analysis, generalized estimating equations, and mixed effect models. For each analytic strategy, we describe appropriate situations to use the method and provide an example that demonstrates the use of the method. Clinical data related to alcohol consumption and HIV are used to illustrate these methods.

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Association of Alcohol Consumption and HIV Surrogate Markers in Participants of the Swiss HIV Cohort Study

Cited by 53 publications

References 39 publications

Alcohol dependence and CD4 cell count: is there a relationship?

Alcohol dependence and CD4 cell count: is there a relationship?

Alcohol-antiretroviral therapy interactive toxicity beliefs and daily medication adherence and alcohol use among people living with HIV

Analytic strategies to evaluate the association of time-varying exposures to HIV-related outcomes: Alcohol consumption as an example

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