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Abstract

Background:

Once-daily (QD), combination antiretroviral therapy (ART) can impact the willingness and ability of patients to take medications as directed. The impact of antiretroviral (ARV) drug adherence influenced by single-tablet (STR) versus multi-tablet regimens (MTR) among patients enrolled in the AIDS Drug Assistance Program (ADAP) in a rural environment has not yet been assessed.

Material and Methods:

A retrospective chart review evaluated adherence and outcomes in adult HIV-infected patients enrolled in the ADAP at 2 ambulatory clinics in the Southeast, taking either a QD STR (efavirenz [EFV]/emtricitabine/tenofovir [TDF]) or a QD protease inhibitor (PI)-based, MTR (atazanavir [ATV], ritonavir [RTV], and emtricitabine/TDF) by evaluating pharmacy refill records, patient self-reported adherence, and virologic response.

Results:

A total of 389 patient records were analyzed (STR, n = 165 versus MTR, n = 224). There were more males, a higher percentage of treatment-naive patients, and more patients with a baseline CD4 count of >200 cells/mm³ in the MTR group. Based on refill records, more patients on MTR were >90% adherent (61.6% versus 51.5%, P = .047). In a multivariable analysis, being treatment experienced was a negative predictor (odds ratio [OR] = 0.48, 0.29-0.78) for adherence. Regimen choice was not associated with adherence. More patients taking MTR were virologically suppressed at the end of the observation period. Regardless of the regimen, being >90% adherent was a significant predictor of virologic suppression (OR = 3.51, 1.98-6.23).

Conclusion:

Treatment-experienced patients enrolled in ADAP are less likely to be adherent. A QD PI-based MTR may result in comparable adherence to an STR in a rural HIV-infected population.

Keywords

HIV adherence antiretroviral agents rural health services protease inhibitor

Introduction

Potent combination antiretroviral therapy (ART) is the cornerstone of current HIV treatment. Antiretroviral therapy (ART) adherence is one of the strongest predictors of progression to AIDS and death among people living with HIV/AIDS. Nonadherence to ART compromises medication effectiveness and decreases the likelihood of achieving viral suppression. Quality of life of HIV-infected patients is significantly improved with high rates of ART adherence. Erlen et al¹ demonstrated that patients believed their lives were better after taking ARV drugs and that ART offered them a second chance in life. Paterson and colleagues² showed that an adherence rate of 95% to a protease inhibitor (PI)-based ART regimen is necessary to achieve viral suppression. Others have demonstrated a nonnucleoside reverse transcriptase inhibitor (NNRTI)-based ART regimen may require a slightly lower adherence rate of 70% to 90%.^2,3 Similarly, positive clinical outcomes correlated well with a 90% or higher adherence rate to the integrase strand transfer inhibitors.⁴

Single-tablet regimens (STRs) have proven effective in suppressing viral replication and are the guideline-preferred regimens for treatment-naive patients.⁵ Single-tablet regimens may further increase adherence rates compared with once-daily (QD) multi-tablet regimens (MTRs). In a multicenter, randomized trial investigating the therapeutic switch from a PI- or NNRTI-based MTR to a STR (efavirenz [EFV]/emtricitabine [FTC]/tenofovir [TDF]; Atripla®) in virologically suppressed HIV-infected patients, self-reported adherence was 96% or higher in both groups, with no statistically significant differences between the 2 regimens.⁶ A recent study in a Veteran’s Affairs (VA) population evaluated the impact of ART as STR and MTR on clinical outcomes.⁷ Patients taking STRs had fewer hospitalizations, a 20% greater odds of achieving an undetectable viral load, and were 2 times more likely to be adherent compared to those taking MTRs.

The AIDS Drug Assistance Program (ADAP), a federally funded program that provides ART to low-income, uninsured, or underinsured Americans living with HIV/AIDS, has dispensed more than 450,000 prescriptions (60% ARVs) to more than 135,000 enrollees. Program operations, including dispensing mechanisms (eg, centralized pharmacy versus mail order) and formulary decisions, are handled at the individual state level. Proven barriers to adherence that threaten medication access are common in the ADAP population.⁸ Godwin et al⁹ has shown a medication possession ratio (MPR) of 84% among ADAP users in a single clinic in Alabama with younger age, nonwhite race, and a lower baseline CD4 count all associated with lower adherence rates.

In the Deep South, HIV-related health outcomes are disproportionate compared to national statistics.¹⁰ This may be due to the higher prevalence of patients in rural areas and challenges with access to care. Additional common characteristics among these states include high rates of poverty, lower educational levels, and high rates of comorbid disease states such as heart disease and diabetes.^11,12 In light of the unique adherence barriers in the Deep South, specifically among ADAP enrollees, and mounting data supporting improved adherence rates and clinical outcomes associated with STRs compared with MTRs, the impact of these regimens on adherence in HIV-infected patients warrants evaluation. This study evaluated comparative adherence and virologic outcomes in adult HIV-infected patients enrolled in ADAP at two clinics in labama or South Carolina taking either a STR or MTR, QD ART regimens.

Methods

We performed a multicenter, retrospective, observational cohort study at 2 independent, HIV/AIDS clinics in the Southeast United States. The Immunology Clinic (Study Site A) is a state-funded, Ryan White clinic associated with the University of South Carolina, Department of Internal Medicine in Columbia, South Carolina. It serves 2,000 HIV/AIDS-infected patients, the majority of whom have an income below the federal poverty line and no medical insurance. There are approximately 961 patients receiving ART through ADAP at the Columbia clinic. The Medical AIDS Outreach of Alabama Clinic (Study Site B) is a state and federally funded, Ryan White clinic in Montgomery, Alabama. The clinic medically serves approximately 1,300 patients who are almost evenly distributed between those with and without medical insurance. There are approximately 450 patients receiving ART on ADAP at the Montgomery clinic. We consecutively enrolled patients aged ≥18 years with a documented visit to 1 of the 2 clinics between January 2007 and December 2010, who were prescribed 1 of the 2 QD ARV regimens, that is, a PI-based MTR (FTC) consisting of atazanavir (ATV), boosted with ritonavir (r), and FTC/TDF (Reyataz®/Norvir®/Truvada®) or an NNRTI-based STR, EFV/FTC/TDF. These 2 regimens were selected because EFV/FTC/TDF was the only STR available during the study period, and AZV/r /TDF/FTC consists of the same NRTI components and had the lowest pill burden of the QD boosted-PI regimens at that time. Both regimens were appropriate first-line ART for HIV-1-infected adults according to 2007 guidelines prepared by the Department of Health and Human Services.¹³ Patients were included if they filled their ART through the South Carolina or Alabama ADAP at least twice during the study period. Selection of an ADAP population allowed for directly measured adherence by drug dispensing records in the respective clinics. Patients were excluded from the study if they were prescribed ART less frequently than once a day.

The following data were collected on each study participant for up to 24 consecutive months: patient adherence determined by computerized pharmacy refill records and patient self-reporting of missed doses at each medical visit as documented by the nursing intake; patients’ age, gender, and race; number of concomitant medications and ARV regimen; and treatment status. Treatment status was divided into treatment experienced or naive. Treatment experienced was defined as previous history of taking ART including one of the study ARV regimens any time before the day of study inclusion. Treatment naive was defined as no prior history of ART exposure and initiating ART with one of the study regimens during the study period. Viral load (HIV RNA) and CD4 count were recorded for clinic visits throughout the study inclusion period.

Adherence according to pharmacy refill records was recorded as the average number of days between monthly refills. Adherence according to self-reporting was estimated by assuming that each day of ART missed was an additional day between refills of a 30-day supply. The adherence rate for each study participant was calculated using MPR by calculating the percentage of days missed out of 30 days and subtracting from 100%.

An adherence rate greater than 90% was used to categorize a patient as sufficiently adherent to ART in accordance with the previous studies.^2
–4 An HIV RNA of ≦75 or ≦50 copies/mL, depending on the assay available at the Immunology Clinic and Medical AIDS Outreach clinic, respectively, during the study period, was defined as undetectable. The number of patients in each treatment group with undetectable HIV RNA at the end of study was calculated. In addition, the percentage of time of undetectable HIV RNA for each participant was calculated and compared between treatment groups. The mean change in CD4 count was compared between adherent and nonadherent patients and between treatment groups.

Patients’ demographics and basic clinical outcomes were compared between the 2 treatment groups. Categorical variables were compared with chi-square or Fisher exact tests, as appropriate. Continuous variables were not normally distributed and compared with Mann-Whitney U tests. A multivariable logistic regression model was used to evaluate factors associated with adherence. A multivariable regression was also performed to evaluate the impact of adherence on patients’ virologic suppression defined as undetectable HIV RNA, as well as to predict the probability of achieving virologic suppression. The statistical significance level was defined as a P value of <.05. All analyses were performed using SAS Software version 9.2 (Statistical Analysis Systems, Cary, North Carolina).

Results

Baseline Characteristics

A total of 389 patients met the inclusion criteria for this analysis, that is, 224 (57.6%) in the MTR group and 165 (42.4%) in the STR group (Table 1). Patients had a median age of 42 years, were predominantly African American, and were >60% were male. Patients were taking an average of 2.5 concomitant medications, and 46% were taking up to 4 concomitant medications. At baseline, ≥75% of patients had an undetectable viral load. The median CD4 count was 360 and 296 cells/mm³, in the MTR and STR groups, respectively (P < .0087), and the percentage of patients with a baseline CD4 count < 200 cells/mm³was 21% and 31%, respectively. The median duration of follow-up was 22 and 14 months in the MTR and STR groups, respectively (P < .001). Patients were predominately treatment experienced (69.2%) prior to the study. More of these patients were prescribed the STR (78% and 63%, P = .0009), whereas more treatment-naive patients were prescribed the MTR (38% and 22%, respectively, P = .0009).

Table 1.

Baseline Characteristics of the Study Participants by Regimen Status.^a

	Single-Tablet Regimen, n = 165	Multi-Tablet Regimen, n = 224	P Value
Age (median)	43.0 (IQR 13.0)	42.0 (IQR 17.0)	.3314
Race			.1342
Black	73.3	80.4
White	20.6	12.5
Hispanic	3.0	4.9
Other	3.0	2.2
Gender			.0028
Male	61.8	75.9
Female	38.2	24.1
Months of enrollment (median)	14.0 (IQR 14.0)	22.0 (IQR 11.0)	<.0001
Median baseline VL, copies/mL	103.0 (IQR 6572.5)	74.0 (IQR 1326.5)	.0690
Median baseline CD4, cells/mm³	296.0 (IQR 302.0)	360.0 (IQR 295.0)	.0087
Proportion with baseline CD4 count <200 cells/mm³, %	31.5	21.0	.0184
Proportion with undetectable VL,^b %	74.7	82.7	.0553
Antiretroviral treatment history			.0009
Naive	21.8	37.5
Experienced	78.2	62.5
Number of concomitant medications			.6837
0-1	37.0	39.3
2-4	46.1	46.9
>4	17.0	13.8

Abbreviations: IQR, interquartile range; VL, viral load.

^aData are percentage of participants, unless indicated otherwise.

^bUndetectable defined as <75 or <50 copies/mL for the respective clinics.

Adherence Comparisons and Clinical Comparisons between Regimens

Median adherence rates based on clinic records were similar between groups, that is, 91% and 93% in the STR and MTR groups, respectively (P < .14; Table 2). Median self-reported adherence rates were higher than recorded by refill records for both groups (100% and 99%, respectively), and a much higher proportion in the MTR compared to the STR group (93% and 85%, P = .02). The median change in CD4 count from baseline was higher for the MTR group (80 and 53, respectively) but not statistically significant. Numerically, more treatment-experienced patients taking the STR were virologically undetectable at the end of the study (75% and 62%, respectively). Virologic suppression was observed in more treatment-naive patients taking the MTR (39% and 25%, respectively).

Table 2.

Adherence and Other Clinical Differences by Regimen Status.

	Single-Tablet Regimen		Multi-Tablet Regimen		P Value
	N	%	N	%	P Value
Adherence rate by refill records, median	90.5 (IQR 25.0)		93.0 (IQR 16.9)		.1413
No^a	80	48.5	86	38.4	.0467
Yes^b	85	51.5	138	61.6	.0467
Self-reported adherence rate, median	99.2 (IQR 5.1)		100.0 (IQR 2.0)		.0048
No^a	24	14.6	16	7.2	.0179
Yes^b	140	85.4	206	92.8	.0179
Median change in CD4 count from baseline to the end of the study, cells/mm³	53.0 (IQR 179.0)		80.0 (IQR 222.0)		.8509
Undetectable VL at the end of the study	121	73.3	182	81.3	.0553
Treatment-experienced patients	91	75.2	112	61.5	.0518
Treatment-naive patients	30	24.8	70	38.5	.0134

Abbreviations: IQR: interquartile range; VL, viral load.

^a<90% nonadherence.

^b≥90% adherence.

Based on clinic refill records, more treatment-naive patients were >90% adherent with the MTR (44% and 24%, P = .003; Table 3). Alternatively, more treatment-experienced patients were adherent with the STR (77% and 57%, respectively). Patients taking the MTR with an adherence rate <90% had a greater percentage of time undetectable and more patients were virologically suppressed. In patients with >90% adherence, the proportion of patients achieving a CD4 count of >200 cells/mm³ was comparable between regimens. However, in those who were <90% adherent, more patients taking the MTR had a CD4 count of >200 cell/mm³ (78% and 54%, respectively). The median number of concomitant medications was similar between the STR and MTR groups, regardless of the adherence status.

Table 3.

Clinical Characteristics by Adherence Status.

	≥90% Adherence (Refill Records)			<90% Adherence (Refill Records)
	Single-Tablet Regimen	Multi-Tablet Regimen	P Value	Single-Tablet Regimen	Multi-Tablet Regimen	P Value
Antiretroviral treatment history, n (%)			.0026			.2339
Naïve	20 (23.5)	60 (43.5)		16 (20.0)	24 (27.9)
Experienced	65 (76.5)	78 (56.5)		64 (80.0)	62 (72.1)
VL, n (%)			.5303			.0262
Undetectable^a	75 (90.4)	120 (87.6)		46 (58.2)	62 (74.7)
Median time VL undetectable, %	90.9	89.4	.7198	45.5	76.9	.0343
Median change in CD4 count from baseline	74.0	94.0	.2531	32.0	72.5	.3231
CD4, n (%)			.6271			.0010
<200	15 (17.7)	28 (20.3)		37 (46.2)	19 (22.1)
≥200	70 (82.4)	110 (79.7)		43 (53.8)	67 (77.9)
Median # concomitant medications	2.0	2.0	.7180	2.0	1.0	.0798

Abbreviations: IQR, interquartile range; VL, viral load.

^aUndetectable defined as <75 or <50 copies/mL for the respective clinics.

A multivariable analysis was performed to determine predictors for adherence (Table 4). The greatest predictor of adherence was treatment status. Treatment-experienced patients were 52% less likely than treatment-naive patients to be adherent. The regimen, number of concomitant medications, demographic characteristics, baseline CD4 count, or duration of enrollment was not predictive of adherence in this study.

Table 4.

Predictors for Adherence.^a

Predictors	Odds Ratio	95% Confidence Intervals
Regimen
Single-tablet regimen	Reference
Multi-tablet regimen	1.33	(0.85-2.10)
Treatment status
Naive	Reference
Experienced	0.48	(0.29-0.78)
Concomitant medication	0.94	(0.85-1.04)
Sex
Male	Reference
Female	1.16	(0.72-1.87)
Age	1.02	(0.99-1.04)
Race
Black	2.12	(0.52-8.54)
White	0.97	(0.27-3.56)
Hispanic	1.47	(0.27-7.91)
Other	Ref
Baseline CD4	1.00	(1.00-1.00)
Months enrolled	1.01	(0.98-1.05)

^aSignificance level is set at P < .05.

Predictors for virologic suppression including adherence were evaluated (Table 5). Patients adherent to ART were 3-fold more likely than nonadherent patients to be virologically suppressed (odds ratio [OR], 3.51; 95% confidence interval [CI], 1.98-6.23). Virologic suppression was also related to longer enrollment periods during the study (OR, 1.06; 95% CI, 1.02-1.10). Treatment status, baseline CD4 count, or demographic characteristics did not impact virologic suppression. Interestingly, 1 more concomitant medication resulted in a 14% less possibility of virologic suppression (OR, 0.86; 95% CI, 0.76-0.97).

Table 5.

Predictors for Virologic Suppression.^a,b

Predictors	Odds Ratio	95% Confidence Intervals
Adherence
≥90% adherence	3.51	(1.98-6.23)
<90% adherence	Reference
Regimen
Single-tablet regimen	Reference
Multi-tablet regimen	1.11	(0.62-1.99)
Treatment status
Naive	Reference
Experienced	0.55	(0.29-1.07)
Concomitant medication	0.86	(0.76-0.97)
Sex
Male	Reference
Female	0.96	(0.52-1.79)
Age	1.00	(0.98-1.04)
Race
Black	0.31	(0.03-2.95)
White	0.35	(0.04-3.00)
Hispanic	0.20	(0.02-2.54)
Other	Ref
Baseline CD4	1.00	(1.00-1.00)
Months enrolled	1.06	(1.02-1.10)

^aSignificance level is set at P < .05.

^bVirologic suppression defined as HIV RNA <75 or <50 copies/mL for the respective clinics.

Discussion

It is well established that adherence to ART directly impacts morbidity and mortality.^14,15 Nonadherence to ART may further result in the selection of drug-resistant HIV strains.^16
–18 Interdisciplinary teams including pharmacists contribute to higher adherence rates.^19
–21 Both clinics in this study utilize pharmacists for ART adherence counseling. Direct methods of measuring adherence such as direct observation and therapeutic drug monitoring yield a more reliable assessment of adherence; however, these approaches are often cost-prohibitive.¹⁸ Indirect methods of measuring adherence such as electronic monitoring devices, prescription refill histories, and self-reporting are commonly used adherence measurements.^22
–24 Previous studies have reported a moderate to high concordance of self-report and pharmacy refill records.^24

–30 Our study revealed a higher mean self-reported adherence rate (95% and 97%) than clinic refill records (84% and 87%), which was consistent between the treatment groups. Of the variables that impact virologic suppression in this study, adherence was found to be the primary factor influencing this clinical outcome (3-fold higher rates). Godwin et al⁹ also observed low rates of ADAP utilization, particularly in black, younger patients with a history of alcohol abuse. In their study, the mean MPR was 77%, and only 32% of patients were >90% adherent.

The ARV regimen selected may also affect treatment adherence. Studies evaluating the simplification of regimens by reducing pill burden or changing dosing administration to QD have demonstrated greater adherence rates and comparable or improved virologic outcomes.^31

–35 Simplifying regimens from multiple daily doses to QD can positively affect the quality of life.^32,36 Reducing pill burden to a QD regimen has also achieved greater optimal (>95% adherence) rates and higher patient satisfaction.^33

–38 Single-tablet regimens have demonstrated high adherence rates and noninferiority in maintaining virologic suppression^35,38 These outcomes, associated with the simplification of ART, have been largely studied with EFV-based regimens, but PI-based regimens have also been evaluated. Several ATV studies in treatment-naive patients reported very high adherence rates to TDF/emtricitabine/ATV/RTV and positive satisfaction with the regimen.^39,40 In a meta-analysis by Parienti et al, adherence was greater for patients who were initiating therapy compared with those who were switching to QD regimens.³¹ In our study, both QD regimens had mean adherence rates >84%; Compared to STR, MTR overall had higher rates of adherence (>90%) and specifically in treatment-naive patients.

Studies of virologic failure among ART regimens indicate that different classes of ART appear to have different adherence cutoff rates resulting in regimen failure.^41
–43 In a prospective, cohort study evaluating low, moderate, and high adherence rates with ART, moderate levels of adherence to NNRTI-based regimens maintained virologic suppression, and low adherence resulted in virologic failure⁴¹ Comparatively, moderate adherence to unboosted and boosted PI regimens resulted in virologic failure, while an adherence rate of >95% correlated with a 70% lower risk of virologic failure in patients taking PI therapy.² Intermediate rates of adherence (70%-90%) with NNRTI appear to be more forgiving.^3,42 This is considered to be due to their long half-lives and higher trough concentrations above the level of resistance (inhibitory quotient).⁴¹ This relationship of adherence to ARV failure is important to consider in individualizing therapy.

Health outcomes in HIV-infected patients in the Deep South are particularly affected by unique barriers related to the rural living circumstances.⁴⁴ This population characteristically is more impoverished, has lower levels of education, transportation limitations, poor access to health care resources, preventive health services, and health information and is subject to greater social stigma.^10,11,45,46 These aspects present additional challenges to achievement of optimal health outcomes with ART. In our study of patients from 2 clinics in the southern states, the MTR resulted in greater durability of response as compared with the STR. Refill records indicated greater adherence to the MTR (mean adherence rate of 88%). In this more treatment-experienced population, more patients taking the MTR were virologically suppressed regardless of adherence rates with greater durability of response. Greater time of virologic suppression observed with this regimen may have been due to the greater proportion of patients taking the MTR compared with those taking the STR. Of those who were undetectable on ART at baseline, more patients on the MTR remained virologically suppressed during this study. Antiretroviral medications obtained through the ADAP are provided at no cost to the patients, so financial burden would not be a concern with the patients studied. The adherence and clinical outcomes observed in our study favored the MTR rather than the STR as previously reported by Rao and colleagues in a VA population.⁷ This may, in part, be attributed to this unique rural population.⁴⁷

Not surprisingly, the number of concomitant medications negatively impacted the achievement of virologic suppression. The challenges of multiple medical conditions and treatment adherence can impact clinical outcomes in HIV-infected patients. The impact of concomitant medications was not unexpected in our population from the Deep South among states with the highest incidences of diabetes and cardiovascular disease.¹² Our study did not find a significant impact of STR compared to MTR as a predictor of virologic outcomes. Additional factors that could account for this are patients living in rural areas with a low educational level, poor health literacy, and limited access to care.^10,11

Several limitations in the present study warrant discussion. First, this is an observational study conducted in 2 HIV/AIDS clinics in the southeast. It is uncertain whether the results can be generalized to other clinical settings. Second, data were obtained retrospectively from medical charts for self-reporting and refill records. Self-reported adherence records are convenient, but they are subject to recall bias and response bias. Third, there were a greater number of patients on the PI-based MTR. Finally, other factors should be further evaluated as barriers to adherence. These include medication side effects; length of time since diagnosis to evaluate pill fatigue; and barriers unique to a rural population such as transportation, poverty, health literacy, low educational level, and retention in care.

Conclusion

Adherence to ART is critical to the durability of virologic and immunologic response. Treatment-experienced patients receiving ADAP ART are less likely to exhibit >90% adherence, regardless of the regimen. In the Southeastern United States, QD, PI-based MTR may result in comparable adherence to NNRTI-based STR. Evaluation of adherence barriers among ADAP users should continue to be a focus of interdisciplinary teams and state agencies.

Footnotes

Acknowledgment

The authors acknowledge Matthew Caudle, PharmD candidate, for his contributions.

Authors’ Note

Data were presented at the American College of Clinical Pharmacy Annual Meeting, Hollywood, FL, October 21-24, 2012. Abstract #387. At the time of the data collection, Sarah Tennant was a pharmacy student at the South Carolina College of Pharmacy, University of South Carolina.

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: E. Kelly Hester: Speaker’s bureau for ViiV Healthcare. P. Brandon Bookstaver: Advisory board for Gilead.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Erlen

Mellors

. Adherence to combination therapy in persons living with HIV: balancing the hardships and the blessings. J Assoc Nurses AIDS Care. 1999;10(4):75–84.

Paterson

Swindells

Mohr

. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 2000;133(1):21–30.

Nachega

Hislop

Dowdy

. Adherence to nonnucleoside reverse transcriptase inhibitor-based HIV therapy and virologic outcomes. Ann Intern Med. 2007;146(8):564–573.

Mena

Blanco

Cordoba

. A pilot study assessing raltegravir QD versus BID in HIV patients included in a simplification trial. Presented at: 49th ICAAC. Sa Francisco, CA, September 12-15, 2009. Web site. http://www.natap.org/2009/ICCAC/ICCAC_22.htm. Accessed October 11, 2014.

Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the Use of Antiretroviral Agents in HIV-1-Infected Adults and Adolescents. What to Start: Initial Combination Therapy Regimens for the Antiretroviral-Naïve Patient. Rockville, MD: Department of Health and Human Services; 2014:1–285, F–1. Web site. http://aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL.pdf. Updated May 1, 2014. Published May 1, 2014. Accessed June 5, 2014.

Hodder

Mounzer

DeJesus

. Patient-reported outcomes in virologically suppressed, HIV-1-infects subjects after switching to a simplified, single-tablet regimen of efavirenz, emtricitabine, and tenofovir DF. AIDS Patient Care STDs. 2010;24(2):87–96.

Rao

Sutton

Hardin

. Impact of highly active antiretroviral therapy regimen on adherence and risk of hospitalization in veterans with HIV/AIDS. In: 53rd Interscience Conference on Antimicrobial Agents and Chemotherapy, Denver, CO, September 10-13, 2013. Abstract H-1464; 2013.

National ADAP Monitoring Project Annual Report. Web site. http://www.nastad.org. Updated January 2014. Published February 11, 2014. Accessed May 28, 2014.

Godwin

Willig

Nevin

. Underutilization of the AIDS Drug Assistance Program: associated factors and policy implications. Health Serv Res. 2011;46(3):982–995.

10.

Reif

Geonnotti

Whetten

. HIV infection and AIDS in the Deep South. Am J Public Health. 2006;96(6):970–973.

11.

US Census Bureau. Historical Poverty Tables. Web site. http://www.census.gov/hhes/www/poverty/data/historical/people.html. Updated September 2014. Published September 16, 2014. Accessed October 11, 2014.

12.

Kaiser Family Foundation. State Health Facts. Available at: http://kff.org/statedata/. Web site. Updated August 28, 2014. Published September 26, 2014. Accessed October 11, 2014.

13.

Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the Use of Antiretroviral Agents in HIV-1-Infected Adults and Adolescents. Rockville, MD: Department of Health and Human Services; 2007:1–136. Web site. http://aidsinfo.nih.gov/contentfiles/AdultandAdolescentGL000721.pdf. Updated December 1, 2007. Published November 30, 2007. Accessed October 11, 2014.

14.

Garcia de Olalla

Knobel

Carmona

Guelar

López-Colomés

Caylà

. Impact of adherence and highly active antiretroviral therapy on survival in HIV-infected patients. J Acquir Immune Defic Syndr. 2002;30(1):105–110.

15.

Mannheimer

Friedland

Matts

Child

Chesney

. The consistency of adherence to antiretroviral therapy predicts biologic outcomes for human immunodeficiency virus-infected persons in clinical trials. Clin Infect Dis. 2002;34(8):1115–1121.

16.

Montaner

Reiss

Cooper

. A randomized, double-blind trial comparing combinations of nevirapine, didanosine, and zidovudine for HIV-infected patients: the INCAS Trial. Italy, The Netherlands, Canada and Australia Study. JAMA. 1998;279(12):930–937.

17.

Vanhove

Schapiro

Winters

Merigan

Blaschke

. Patient compliance and drug failure in protease inhibitor monotherapy. JAMA. 1996;276(24):1955–1956.

18.

Osterberg

Blaschke

. Adherence to medication. N Engl J Med. 2005;353(5):487–497.

19.

Chen

Chau

Saberi

. Improving adherence and clinical outcomes through an HIV pharmacist's interventions. AIDS Care. 2010;22(10):1189–1194.

20.

Krummenacher

Cavassini

Bugnon

Schneider

. An interdisciplinary HIV-adherence program combining motivational interviewing and electronic antiretroviral drug monitoring. AIDS Care. 2011;23(5):550–561.

21.

Rathbun

Farmer

Stephens

Lockhart

. Impact of an adherence clinic on behavioral outcomes and virologic response in treatment of HIV infection: a prospective, randomized, controlled pilot study. Clin Ther. 2005;27(2):199–209.

22.

Farmer

. Methods for measuring and monitoring medication regimen adherence in clinical trials and clinical practice. Clin Ther. 1999;21(6):1074–1090; discussion 1073.

23.

Garber

Nau

Erickson

Aikens

Lawrence

. The concordance of self-report with other measures of medication adherence: a summary of the literature. Med Care. 2004;42(7):649–652.

24.

Cook

Wade

Martin

Perri

III . Concordance among three self-reported measures of medication adherence and pharmacy refill records. J Am Pharm Assoc. 2005;45(2):151–159.

25.

Kastrissios

Suarez

Katzenstein

Girard

Sheiner

Blaschke

. Characterizing patterns of drug-taking behavior with a multiple drug regimen in an AIDS clinical trial. AIDS. 1998;12(17):2295–2303.

26.

Levine

Hinkin

Marion

. Adherence to antiretroviral medications in HIV: differences in data collected via self-report and electronic monitoring. Health Psychol. 2006;25(3):329–335.

27.

Llabre

Weaver

Duran

Antoni

McPherson-Baker

Schneiderman

. A measurement model of medication adherence to highly active antiretroviral therapy and its relation to viral load in HIV-positive adults. AIDS Patient Care STDs. 2006;20(10):701–711.

28.

Pearson

Simoni

Hoff

Kurth

Martin

. Assessing antiretroviral adherence via electronic drug monitoring and self-report: an examination of key methodological issues. AIDS Behav. 2007;11(2):161–173.

29.

Hugen

Langebeek

Burger

. Assessment of adherence to HIV protease inhibitors: comparison and combination of various methods, including MEMS (electronic monitoring), patient and nurse report, and therapeutic drug monitoring. J Acquir Immun Defic Syndr. 2002;30(3):324–334.

30.

Arnsten

Demas

Farzadegan

. Antiretroviral therapy adherence and viral suppression in HIV-infected drug users: comparison of self-report and electronic monitoring. Clin Infect Dis. 2001;33(8):1417–1423.

31.

Parienti

Bangsberg

Verdon

Gardner

. Better adherence with once-daily antiretroviral regimens: a meta-analysis. Clin Infect Dis. 2009;48(4):484–488.

32.

Molina

Journot

Morand-Joubert

. Simplification therapy with once-daily emtricitabine, didanosine, and efavirenz in HIV-1-infected adults with viral suppression receiving a protease inhibitor-based regimen: a randomized trial. J Infect Dis. 2005;191(6):830–839.

33.

Jayaweera

Dejesus

Nguyen

Grimm

Butcher

Seekins

. Virologic suppression, treatment adherence, and improved quality of life on a once-daily efavirenz-based regimen in treatment-Naive HIV-1-infected patients over 96 weeks. HIV Clinical Trials. 2009;10(6):375–384.

34.

Buscher

Hartman

Kallen

Giordano

. Impact of antiretroviral dosing frequency and pill burden on adherence among newly diagnosed, antiretroviral-naive HIV patients. Intern J STD AIDS. 2012;23(5):351–355.

35.

Dejesus

Young

Morales-Ramirez

. Simplification of antiretroviral therapy to a single-tablet regimen consisting of efavirenz, emtricitabine, and tenofovir disoproxil fumarate versus unmodified antiretroviral therapy in virologically suppressed HIV-1-infected patients. J Acquir Immun Defic Syndr. 2009;51(2):163–174.

36.

Campo

Cohen

Grimm

Shangguan

Maa

Seekins

. Switch from protease inhibitor- to efavirenz-based antiretroviral therapy improves quality of life, treatment satisfaction and adherence with low rates of virological failure in virologically suppressed patients. Intern J STD AIDS. 2010;21(3):166–171.

37.

DeJesus

Ruane

McDonald

. Impact of switching virologically suppressed, HIV-1-infected patients from twice-daily fixed-dose zidovudine/lamivudine to once-daily fixed-dose tenofovir disoproxil fumarate/emtricitabine. HIV Clinical Trials. 2008;9(2):103–114.

38.

Airoldi

Zaccarelli

Bisi

. One-pill once-a-day HAART: a simplification strategy that improves adherence and quality of life of HIV-infected subjects. Patient Prefer Adherence. 2010;4:115–125.

39.

Elion

Cohen

Ward

. Evaluation of efficacy, safety, pharmacokinetics, and adherence in HIV-1-infected, antiretroviral-naive patients treated with ritonavir-boosted atazanavir plus fixed-dose tenofovir DF/emtricitabine given once daily. HIV Clinical Trials. 2008;9(4):213–224.

40.

Parienti

Barrail-Tran

Duval

. Adherence profiles and therapeutic responses of treatment-naive HIV-infected patients starting boosted atazanavir-based therapy in the ANRS 134-COPHAR 3 trial. Antimicrob Agents Chemother. 2013;57(5):2265–2271.

41.

Maggiolo

Airoldi

Kleinloog

. Effect of adherence to HAART on virologic outcome and on the selection of resistance-conferring mutations in NNRTI- or PI-treated patients. HIV Clin Trials. 2007;8(5):282–292.

42.

Maggiolo

Ravasio

Ripamonti

. Similar adherence rates favor different virologic outcomes for patients treated with nonnucleoside analogues or protease inhibitors. Clin Infect Dis. 2005;40(1):158–163.

43.

Le Moing

Chene

Carrieri

. Predictors of virological rebound in HIV-1-infected patients initiating a protease inhibitor-containing regimen. AIDS. 2002;16(1):21–29.

44.

Amico

Konkle-Parker

Cornman

. Reasons for ART non-adherence in the deep south: adherence needs of a sample of HIV-positive patients in Mississippi. AIDS Care. 2007;19(10):1210–1218.

45.

Heckman

Somlai

Peters

. Barriers to care among persons living with HIV/AIDS in urban and rural areas. AIDS Care. 1998;10(3):365–375.

46.

Southern AIDS Coalition Southern States Manifesto: update 2012. Web site. http://www.southernaidscoalition.org/Southern+States+Manifesto-+Update+2012.pdf. Updated July 2012. Published July 18, 2012. Accessed March 4, 2014.

47.

Weissman

Duffus

Vyavaharkar

. Defining the rural HIV epidemic: correlations of 3 definitions—South Carolina, 2005-2011. J Rural Health. 2014;30(3):275–283.

Adherence among Rural HIV-Infected Patients in the Deep South

Abstract

Background:

Material and Methods:

Results:

Conclusion:

Keywords

Introduction

Methods

Results

Baseline Characteristics

Adherence Comparisons and Clinical Comparisons between Regimens

Discussion

Conclusion

Footnotes

Acknowledgment

Authors’ Note

Declaration of Conflicting Interests

Funding

References