An alternative methodology for the prediction of adherence to anti HIV treatment.

School of Life Sciences, Kingston University, Penrhyn Road, Kingston-upon-Thames, KT1 2EE, UK.
AIDS Research and Therapy (Impact Factor: 1.84). 02/2009; 6:9. DOI: 10.1186/1742-6405-6-9
Source: PubMed

ABSTRACT Successful treatment of HIV-positive patients is fundamental to controlling the progression to AIDS. Causes of treatment failure are either related to drug resistance and/or insufficient drug levels in the blood. Severe side effects, coupled with the intense nature of many regimens, can lead to treatment fatigue and consequently to periodic or permanent non-adherence. Although non-adherence is a recognised problem in HIV treatment, it is still poorly detected in both clinical practice and research and often based on unreliable information such as self-reports, or in a research setting, Medication Events Monitoring System caps or prescription refill rates. To meet the need for having objective information on adherence, we propose a method using viral load and HIV genome sequence data to identify non-adherence amongst patients.
With non-adherence operationally defined as a sharp increase in viral load in the absence of mutation, it is hypothesised that periods of non-adherence can be identified retrospectively based on the observed relationship between changes in viral load and mutation.
Spikes in the viral load (VL) can be identified from time periods over which VL rises above the undetectable level to a point at which the VL decreases by a threshold amount. The presence of mutations can be established by comparing each sequence to a reference sequence and by comparing sequences in pairs taken sequentially in time, in order to identify changes within the sequences at or around 'treatment change events'. Observed spikes in VL measurements without mutation in the corresponding sequence data then serve as a proxy indicator of non-adherence.
It is envisaged that the validation of the hypothesised approach will serve as a first step on the road to clinical practice. The information inferred from clinical data on adherence would be a crucially important feature of treatment prediction tools provided for practitioners to aid daily practice. In addition, distinct characteristics of biological markers routinely used to assess the state of the disease may be identified in the adherent and non-adherent groups. This latter approach would directly help clinicians to differentiate between non-responding and non-adherent patients.

  • [Show abstract] [Hide abstract]
    ABSTRACT: BACKGROUND: Adherence to treatment remains a key issue for tuberculosis (TB) and human immunodeficiency virus (HIV) programs. The study objective was to identify potential determinants of medication adherence (MA) among patients with TB, HIV, or both. METHODS: In this cross-sectional study, adult patients attending TB or HIV clinics were recruited in two main regions (Centre and Hauts-Bassins) of Burkina Faso from August to October 2010. Questionnaires were collected and simple and multiple step-wise linear regression models were used to identify predictors of MA. RESULTS: In total, 1043 patients (309 with TB, 553 with HIV, and 181 coinfected with both) participated in this study. For patients with TB, adjusted predictors of good MA were no alcohol use, ever been lost to follow-up, and awareness of disease transmission. For patients with HIV, adjusted predictors of good MA were less stigma, good knowledge about TB transmission, and awareness of disease transmission. For patients with dual infection, adjusted predictors of good MA was good attitude. Furthermore, adjusted predictors of poor MA for patients with TB or with dual infection were poor financial access to care and high number of persons sleeping in the household, respectively. CONCLUSION: This study provides information on MA in patients infected with TB, HIV, and those coinfected with TB and HIV. TB and HIV programs have to consider the environment of the patient and its characteristics, including stigma, attitude, status of loss to follow-up, TB knowledge, financial access to care, alcohol use, awareness of disease transmission, and number of persons sleeping in the household. These identified factors in this study need to be taken into account for a specific patient profile and during sensitization, project planning, and research stages.
    Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi 06/2013; 47(3). DOI:10.1016/j.jmii.2013.05.001 · 2.08 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Medication non-adherence is a significant health problem. There are numerous methods for measuring adherence, but no single method performs well on all criteria. The purpose of this systematic review is to (i) identify self-report medication adherence scales that have been correlated with comparison measures of medication-taking behaviour, (ii) assess how these scales measure adherence and (iii) explore how these adherence scales have been validated. Cinahl and PubMed databases were used to search articles written in English on the development or validation of medication adherence scales dating to August 2012. The search terms used were medication adherence, medication non-adherence, medication compliance and names of each scale. Data such as barriers identified and validation comparison measures were extracted and compared. Sixty articles were included in the review, which consisted of 43 adherence scales. Adherence scales include items that either elicit information regarding the patient's medication-taking behaviour, and/or attempts to identify barriers to good medication-taking behaviour or beliefs associated with adherence. The validation strategies employed depended on whether the focus of the scale was to measure medication-taking behaviour or identify barriers or beliefs. Supporting patients to be adherent requires information on their medication-taking behaviour, barriers to adherence and beliefs about medicines. Adherence scales have the potential to explore these aspects of adherence, but currently there has been a greater focus on measuring medication-taking behaviour. Selecting the "right" adherence scale(s) requires consideration of what needs to be measured and how (and in whom) the scale has been validated.
    British Journal of Clinical Pharmacology 06/2013; 77(3). DOI:10.1111/bcp.12194 · 3.69 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: HIV treatment requires lifelong adherence to medication regimens that comprise inconvenient scheduling, adverse side effects, and lifestyle changes. Antiretroviral adherence and treatment fatigue have been inextricably linked. Adherence in HIV-infected populations has been well investigated; however, little is known about treatment fatigue. This review examines the current state of the literature on treatment fatigue among HIV populations and provides an overview of its etiology and potential consequences. Standard systematic research methods were used to gather published papers on treatment fatigue and HIV. Five databases were searched using PRISMA criteria. Of 1557 studies identified, 21 met the following inclusion criteria: (a) study participants were HIV-infected; (b) participants were prescribed antiretroviral medication; (c) the article referenced treatment fatigue; (d) the article was published in a peer-reviewed journal; and (e) text was available in English. Only seven articles operationally defined treatment fatigue, with three themes emerging throughout the definitions: (1) pill burden; (2) loss of desire to adhere to the regimen; and (3) nonadherence to regimens as a consequence of treatment fatigue. Based on these studies, treatment fatigue may be defined as "decreased desire and motivation to maintain vigilance in adhering to a treatment regimen among patients prescribed long-term protocols." The cause and course of treatment fatigue appear to vary by developmental stage. To date, only structured treatment interruptions have been examined as an intervention to reduce treatment fatigue in children and adults. No behavioral interventions have been developed to reduce treatment fatigue. Further, only qualitative studies have examined treatment fatigue conceptually. Studies designed to systematically assess treatment fatigue are needed. Increased understanding of the course and duration of treatment fatigue is expected to improve adherence interventions, thereby improving clinical outcomes for individuals living with HIV.
    Psychology Health and Medicine 08/2014; 20(3):1-11. DOI:10.1080/13548506.2014.945601 · 1.53 Impact Factor

Full-text (2 Sources)

Available from
Jun 1, 2014