Medication adherence trends in HIV patients in Gugulethu Community

Medication adherence trends in HIV patients in Gugulethu Community Health Center, South Africa. 2010-2019

Abstract

The discovery of novel antiviral drugs, especially antiretroviral drugs with an upgraded level of tolerance, has led to a drastic change in improving the HIV infection management in the previous years. Patients having early phase of HIV infection and at the chronic stage are not consistent in adhering to recommended antiviral therapy. The emergence of antiviral drug resistance and its spread to other healthy people, along with high morbidity and mortality, are the main reasons behind lacking adherence to antiretroviral therapy. This study aims to determine different trends in the implementation of ART in HIV positive patients. Data from 2010 to 2019 will be collected to understand the adherence and implementation trend to novel ART. To understand the factors influencing the adherence and implementation, a comparison study will be carried between ART implementation in HIV positive patients and control medication implementation in HIV negative people. SAS, version 9.4 by SAS Institute, NC, USA, will be used to perform analyses. Statistical significance will be assessed at 99 percent confidence level by using two-sided tests.

Keywords: HIV, adherence trends, antiretroviral drugs, ART

Introduction

The discovery of innovative antiviral drugs, especially antiretroviral (ART) drugs with an upgraded level of tolerance, has led to a very drastic change in improving the management of Human Immuno Deficiency virus infection (HIV) in the past few decades. All the patients in the United States are recommended to initiate antiretroviral therapy since 2012(Health & Services, 2009). This fatal infection can be transformed into a manageable and treatable infection if patients remain consistent in maintaining a sufficient level of adherence to antiviral therapy (Chaiyachati et al., 2014; Deeks, Lewin, & Havlir, 2013).

Patients with early stage infection of HIV and chronic stage are not consistent in adhering to recommended antiviral therapy (Brown & Bussell, 2011).  The emergence of antiviral drug resistance and its spread to other healthy people, along with high morbidity and mortality, are the main reasons behind lacking adherence to antiretroviral therapy (Chaiyachati et al., 2014). Many interventions and implementations have been done in improving the dose taking regimen of HIV patients (Control & Prevention, 2014). In the United States, most of the HIV health care sources have described antiretroviral adherence problems in HIV patients at every visit to the hospital and clinic premises; more than 50% of the patients were referred to as non-adherent to antiviral therapy (Weiser et al., 2017). There are three phases of medication adherence: initiation, persistence, and implementation (Vrijens et al., 2012). Previously implementation and persistence were not categorized separately, though they represent different but interconnected patients’ behavior (Bae, Guyer, Grimm, & Altice, 2011). A previous study indicated upgraded persistence with antiretroviral therapy in HIV-positive patients between 2009 and 2017 (Youn et al., 2017). Average time to antiretroviral therapy non-persistence raised by two times (from 24 months to 38 months) in last three years, but patients initiating this therapy in 2007-2010 could not maintain this level of persistence because of lacking follow up after 2010.

Objective of this study is to determine different trends in the implementation of ART in HIV positive patients. Data from 2010 to 2019 will be collected to understand the adherence and implementation trend to novel ART. To understand the factors influencing the adherence and implementation, a comparison study will be carried between ART implementation in HIV positive patients and control medication implementation (angiotensin-converting enzyme inhibitors, statins, or metformin) in HIV negative people.

Methodology

Source of Data:

We will use insurance files from 2010 to 2019  from high HIV prevalence regions of the country. These data files will be obtained from any health insurance program serving as the largest care source for HIV patients.

Population under study:

Patients will be categorized into three groups. Group-A will have the HIV positive persons who have started statin, metformin, or ARB/ACEI(angiotensin receptor blocker or angiotensin‐converting enzyme inhibitor). Group-B will comprise of HIV negative persons who have initiated a statin. Group-C will be comprised of HIV-positive persons who started ART (antiretroviral therapy). Each patient will be diagnosed with HIV status as described by (Youn et al., 2017).

For a comprehensive analysis of the start of medication and results, beneficiaries of selected beneficiaries will have insurance coverage from at least one year before their first fill ( washout period) to three years post-initiation (follow-up). The beneficiaries having a history of respective medication for less than one month will also be excluded.

For group A, beneficiaries using incomplete ART regimen, i.e., under different three antiretroviral components, will be eliminated. For group C, only those beneficiaries will be considered for this study who will meet the criteria of having HIV before starting statin medication.

Quantification of CD4+ cells:

The blood will be collected from both HIV+ and HIV+ NCDs study groups to quantify CD4+ T lymphocytes with the help of flow cytometry. For this purpose, density centrifugation will be done to isolate peripheral blood mononuclear cells (PBMC). The PBMC will be stimulated by incubating them with co-stimulatory antibody against CD4+ and specific peptides of HIV. The CD4+ cells then will be quantified by using six- parameter flow cytometric analysis. Result obtained from both groups will be then compared critically.

Quantification of HIV viral load:

The HIV viral load will be determined by a new ultrasensitive real time polymerase chain reaction. After RNA extraction from the plasma of the patients under 2 study groups, qRT- PCR will be perform for the long terminal repeat region (LTR) of the HIV virus. The viral load of both study groups will be compared and analyzed.

Quantification of NCDs parameters:

A comparative analysis of HbA1c (glycated haemoglobin) level and blood pressure of the patients in both study groups will also be carried out.

Comparison of medication frequency/Assessment of adherence:

Methods and definitions recommended by the EMERGE guidelines will be followed to analyze medication adherence/frequency in two years after starting the medication (De Geest et al., 2018). To create each medication implementation rate, filled and supplied dates will be used from each therapeutic class. The implementation rate will be dichotomized by using a 90 percent cut off along with sensitivity assessment. According to current studies, for newer ART therapies, a lower adherence level can be enough compared to 95 percent needed for previous ART therapies (Kobin & Sheth, 2011).

To permit the switching (for example switching from ACEI to ARB or switching ART ingredients), patients will continue to collect medication usage days for the period they continue to get an agent from the same therapeutic category.

Results

This research will have two investigative approaches. First of all, to identify that if there are any secular trends for general medication adherence contributing to ART implementation trends, we will compare the implementation of ART with control medication implementation. Secondly, the implementation of control medication in HIV positive will be compared with HIV positive persons taking and not taking ART to identify the association of ART therapy engagement with non-ART medication implementation.

Descriptive statistics will be calculated for HIV-positive persons who started ART by the calendar year of initiation. Variations in baseline attributes by HIV status and different medication categories will be assessed for the persons using a statin, metformin, or ARB/ACEI. The proportion of persons with more than 90 percent implementation changed over time will be analyzed to conduct unadjusted analyses. Differences in the ratio of HIV positive and HIV negative persons with more than 90 percent implementation in each year and mean variation across years will be obtained for control medications. Multivariable logistic models for each treatment initiation year, regiment characteristics, patients included, and medication will be implemented for adjusted analyses. Interaction between treatment initiation year and HIV status and indicators of HIV status will also be included for statins. Statistical significance will be assessed at 99 percent confidence level by using two-sided tests. SAS version 9.4 by SAS Institute, NC, USA, will be used to perform analyses.

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