Hanna, David B. PhD*; Hessol, Nancy A. MSPH†; Golub, Elizabeth T. PhD‡; Cocohoba, Jennifer M. PharmD†; Cohen, Mardge H. MD§; Levine, Alexandra M. MD‖; Wilson, Tracey E. PhD¶; Young, Mary MD#; Anastos, Kathryn MD*,**; Kaplan, Robert C. PhD*
Among HIV-infected people who are prescribed potent antiretroviral therapy (ART), treatment adherence is important to maximize its health benefits with respect to virologic suppression and prevention of disease progression.1,2 However, it is well known that adherence can be hampered by many factors including dosing requirements, side effects, and behavioral and psychosocial factors that serve as barriers to optimal use, such as substance use and depression.3,4 Characteristics associated with race/ethnicity have also been associated with adherence, with African Americans less likely than other groups to report optimal adherence to ART.5–7
A lower daily pill burden has been associated with better adherence and treatment outcomes.8,9 One notable innovation among potent ART regimens was the introduction of a once-daily fixed-dose coformulation in 2006 combining tenofovir (TDF), emtricitabine (FTC), and efavirenz (EFV), which reduced the potential pill burden and dosing frequencies required of earlier ART regimens.10 Two additional once-daily combination pills retaining the TDF/FTC backbone but replacing EFV with 1 or more agents have since become available in the United States: a coformulation containing rilpivirine (RPV) in 2011,11 and a coformulation containing elvitegravir (EVG) and the boosting agent cobicistat (COBI) in 2012.12 These new coformulations offer single-tablet regimen alternatives for women planning to become pregnant by replacing EFV, which may have the potential to cause fetal harm.13,14
A few studies have shown single-tablet regimens to either maintain or increase treatment adherence. A multicenter clinical trial of 166 treatment experienced virologically suppressed individuals in the United States found that switching to a single-tablet ART regimen helped patients maintain adherence and increased some aspects of quality of life (QOL).15,16 In an observational cohort study of 118 homeless or unstably housed individuals in San Francisco, taking a single-tablet regimen was associated with greater adherence and viral suppression compared with a multiple-tablet regimen.17 The generalizability of these findings to women has not been fully established because these studies were comprised mostly of men. Numerous studies report lower adherence in women,5,6,18 possibly related to higher toxicity profiles, a higher prevalence of depression, or competing demands such as childcare responsibilities.19–21 The extent to which adherence in women may be affected by single-tablet regimen use in the context of these factors is unknown.
Given the limited data on use of these therapies and their influence on adherence in US women, we examined semiannual trends in single-tablet regimen use and adherence among ART-treated HIV-infected women in the Women's Interagency HIV Study (WIHS) between 2006 and 2013. Using a nested cohort study design, we compared the effectiveness of single-tablet versus multiple-tablet regimen use with respect to adherence and related health outcomes, including virologic suppression, disease progression, and QOL using propensity score matching to account for potential confounding by indication in a broad sample of ART-experienced WIHS participants. In a subset of participants who switched from a preexisting regimen to a single-tablet regimen, we conducted a case-crossover study to test for a postswitch increase in adherence and virologic suppression, as an alternate way to account for confounding because each participant's treatment outcomes after switching are compared with her outcomes before switching.
The WIHS is a longitudinal study of more than 4000 HIV-infected and -uninfected women who have been followed at 6-month intervals at 6 US sites, with detailed examinations, specimen collection, and structured interviews assessing health behaviors, medical history, and medication use.22,23 Women were recruited in 3 waves (1994–1995, 2001–2002, 2010–2012) from HIV primary care clinics, hospital-based programs, community outreach sites, women's support groups, and other locations. In contrast to clinic-based cohorts that collect data through routine care, the WIHS is interval based, meaning that visits occur independently of clinical care and therefore capture behaviors (eg, ART nonadherence) that may be less likely to be reported to care providers. The demographic composition of study participants in the WIHS is representative of the US female HIV-infected population.24
Inclusion criteria included HIV infection and ART use. We included any person-visit in the WIHS between April 1, 2006, and March 31, 2013, during which an HIV-infected participant self-reported ART use in the previous 6 months and had a valid HIV-1 viral load measurement. In the time trend analysis only, we excluded ART users who enrolled in the WIHS in 2011 or later (N = 701 person-visits) to avoid a potential cohort effect by this younger group. Because most WIHS participants during the study period are ART experienced, and such individuals differ in adherence levels compared with those who are ART-naive,25 we limited analyses examining the association between single-tablet regimen use and adherence-related outcomes to ART-experienced women.
We conducted sensitivity analyses among a predefined subgroup of women who were less likely to conceive and therefore more likely to be indicated for use of the EFV/TDF/FTC coformulation due to the following characteristics: age 45+, report of having undergone menopause, a history of sterilization (eg, hysterectomy, tubal ligation, or oophorectomy), or use of hormonal birth control in the past 6 months. We also performed a sensitivity analysis excluding RPV/TDF/FTC and EVG/COBI/TDF/FTC users because they only comprised 6% of person-visits on a single-tablet regimen.
Exposure of Interest
Our exposure of interest was single-tablet regimen use, defined as current use of one of the 3 available single-tablet ART formulations (EFV/TDF/FTC, RPV/TDF/FTC, and EVG/COBI/TDF/FTC), and no other antiretroviral drugs at each 6-month study visit.
Outcomes of Interest
ART adherence is assessed in the WIHS by asking the participant the percentage of time during the past 6 months that ART was taken as prescribed,26 categorized as follows: 100% of the time, 95%–99%, 75%–94%, and <75%. We dichotomized the response to 95% or greater adherence based on prior work that has found this level of adherence to optimize virologic outcomes.27 We also examined an alternate definition of 100% adherence versus <100% adherence.28 This decision was supported by WIHS data showing 77%–78% virologic suppression among women reporting either 95%–99% or 100% adherence, but only 60% suppression among women reporting 75%–94% adherence. Virologic suppression was defined as having an HIV-1 viral load <80 copies per milliliter. We assessed QOL based on a summary score derived from a shortened version of the Medical Outcomes Study-HIV.29,30 This score, which comprises 6 subdomains including physical function, pain, energy/fatigue, emotional well being, social functioning, and role functioning, ranges from 0, representing worst QOL, to 100, representing best QOL. We defined improvement in QOL as a dichotomous variable capturing any increase in the QOL score from the previous visit. Finally, incident AIDS-defining clinical events were assessed via self-report at each visit or through matches with cancer or tuberculosis registries using the 1993 Centers for Disease Control and Prevention clinical AIDS definition.31 We also examined a composite outcome of clinical AIDS or death. Death was ascertained based on active follow-up with participants or next of kin or through death registry matches.
We considered the following variables as potential confounders: age at visit, race/ethnicity, calendar year, recruitment period (2010–2012 versus earlier), income, education, employment, insurance status, enrollment in the AIDS Drug Assistance Program, study site, CD4+ count, viral load, number of children, birth of child since last visit, history of sterilization, menopause status, current and past recreational drug use and alcohol use, housing status, and severe depressive symptoms (score ≥23), as assessed by the Center for Epidemiologic Studies Depression Scale.32
We examined time trends in once-daily single-tablet regimen use and in ART adherence for each 6-month period between April 2006 and March 2013. Within each period, the numerator was the number of women in each category (eg, on a single-tablet regimen), and the denominator was the number of women on ART. We tested for time trends using Poisson regression with generalized estimating equations.
Nested Cohort Study
To assess the effectiveness of single-tablet regimen use on adherence-related treatment outcomes, we compared outcomes between person-visits on a single tablet regimen and those not on a single-tablet regimen after propensity score matching to address potential confounding by indication.33 We estimated the propensity score as the predicted probability of being on a single-tablet regimen, given the aforementioned confounders, by logistic regression. Using the propensity score, we matched person-visits of women on a single-tablet regimen with similar person-visits not on a single-tablet regimen to eliminate the association between the confounding factors and use of a single-tablet regimen. Nearest neighbor matching was used for all confounders, except for history of sterilization and recruitment period, for which exact matching was used. We matched each single-tablet regimen person-visit to 3 nonsingle–tablet regimen person-visits for increased efficiency. Adequate balance on confounders was assessed based on an estimate of the standardized bias, defined as the difference in the means of each covariate before and after matching, divided by the standard deviation.34 Standardized bias estimates ranged from <0.001 to 0.067, suggesting that the groups were well balanced on all measured confounders. We used log-binomial regression (or Poisson regression when models did not converge) to estimate risk ratios (RRs) for ART adherence, virologic suppression, improvement in QOL, and an AIDS-defining event at the visit after the index person-visit (ie, 6 months after). We performed sensitivity analyses that stratified on baseline presence of viremia to assess whether baseline viral load played a role in subsequent virologic suppression. Because QOL data in the WIHS are collected at every other visit, we used QOL data from the subsequent visit for person-visits with missing data. All analyses used generalized estimating equations to account for correlated data within individuals.35
In a subset of women who switched from a preexisting regimen to a single-tablet regimen, we tested for a postswitch increase in adherence and virologic suppression among those who remained on the single-tablet regimen for 2 consecutive visits, controlling for time-varying confounders, using a case-crossover study design.36 Only time-varying confounders were needed because we compared outcomes in different person-visits corresponding to the same participant. We did not determine RRs for QOL or AIDS-defining events due to insufficient data. Among those not fully adherent to their ART regimen (ie, <100% adherence), we compared the reasons for missing ART medications while on the preexisting regimen versus the single-tablet regimen using a standardized questionnaire.26
We used SAS 9.3 (SAS Institute, Cary, NC) and R 3.0.2 (R Foundation for Statistical Computing, Geneva, Switzerland), including the MatchIt package for propensity score matching,37 for analysis.
There were 15,523 person-visits between April 2006 and March 2013, representing 1727 ART-treated women, included in this analysis. Briefly, 53% were black, 29% Hispanic, and 15% white. The median age at visit was 47 (interquartile range: 41–52). Seventy-one percent had a history of any recreational drug use (25% injection drugs) and 17% were currently using recreational drugs. Seventy-one percent had an income of $24,000 or less and 19% had a Center for Epidemiologic Studies Depression score of 23+, indicative of severe depressive symptoms. The median CD4+ count at the time of visit was 528 cells per microliter (interquartile range: 346–733), and the median viral load was undetectable (75th percentile = 92 copies/mL). Forty-four percent had a history of sterilization. Among participant visits reporting use of a nonsingle–tablet regimen, 70% were on a protease inhibitor (PI)–based regimen, whereas 26% were on a nonnucleotide reverse transcriptase inhibitor–based regimen. Among participant visits reporting use of a single-tablet regimen, 94.6% were on EFV/TDF/FTC, with 5% on RPV/TDF/FTC and the remainder on EVG/COBI/TDF/FTC. Among the 511 single-tablet regimen users during the study period, 13% were ART-naive when first starting the regimen.
Figure 1 shows trends between 2006 and 2013 in single-tablet regimen use, ART adherence, and virologic suppression among established participants using ART in the WIHS. Use of single-tablet regimens significantly increased from 7% in 2006 to 27% in 2013 (Ptrend < 0.001). During the same period, adherence increased from 78% to 85% (Ptrend < 0.001), whereas virologic suppression increased from 71% to 77% (Ptrend < 0.001). After taking into account the increased use of single-tablet regimens, the calendar-time increases in adherence and virologic suppression were attenuated by 53% and 21%, respectively, suggesting that single-tablet regimens contributed considerably to the increase in adherence over time. These relationships persisted when focusing on women more likely to have no contraindication for EFV/TDF/3TC (75% of the study population), that is, women no longer of childbearing age, sterile women, or women on hormonal contraception.
Among treatment-experienced women, there were 1846 person-visits between 2006 and 2013 on a single-tablet regimen available for the nested cohort study, propensity-score matched on a 1:3 basis with 5348 person-visits on a multiple-tablet regimen. Table 1 shows selected characteristics of women at these visits, before and after matching. Being on a single-tablet regimen was associated with a 5% increase in adherence, defined as taking one's medications at least 95% of the time during the previous 6 months (adjusted RR: 1.05, 95% confidence interval (CI): 1.03 to 1.08) (Table 2). Defining adherence as taking one's medications 100% of the time resulted in a larger association (RR: 1.18, 95% CI: 1.10 to 1.26).
A single-tablet regimen was also significantly associated with increased virologic suppression (RR: 1.06, 95% CI: 1.01 to 1.11). This association was maintained when stratifying by viremia: among those with no detectable viremia when the regimen was assessed, the RR for maintaining suppression was 1.04 (95% CI: 1.01 to 1.07); among those with viremia, the RR for becoming suppressed was 1.19 (95% CI: 1.02 to 1.39). Single-tablet regimen use was associated with better QOL and fewer AIDS-defining events in the next 6 months, but these results were not statistically significant (RR: 1.03, 95% CI: 0.96 to 1.11 and RR: 0.96, 95% CI: 0.62 to 1.49, respectively). Extending follow-up of AIDS-defining events to 2 years resulted in a more pronounced effect (RR: 0.61, 95% CI: 0.37 to 0.996). These inferences remained when excluding RPV/TDF/FTC and EVG/COBI/TDF/FTC from analysis.
TABLE 1-b Demographi...Image Tools
For the case-crossover study, there were 163 women who switched regimens over time and maintained single-tablet regimen use for at least 2 visits. Thirty-five percent of these women were previously on the same drug components before switching to the single-tablet regimen (eg, TDF/FTC + EFV) and 28% had been on a similar regimen based on the same drug class (ie, 2 NRTI + 1 non-nucleotide reverse transcriptase inhibitor) before switch. Fifty-eight percent had been on a regimen based on a different drug class, primarily PI based. Thirty-four percent had been on a twice- or 3 times daily regimen before switching to a single-tablet regimen. The single-tablet regimen was associated with increased adherence (from 85%–90%, RR: 1.08, 95% CI: 1.002 to 1.14) and virologic suppression (from 77%–85%, RR: 1.08, 95% CI: 0.97 to 1.20) compared with levels on the prior regimen (Table 3). Important time-varying characteristics associated with better outcomes included a higher baseline CD4+ count, less alcohol use, and no recreational drug use. Seventy percent of switchers maintained their baseline viral load after switching, whereas 18% had a lower viral load and 12% had a higher viral load. Among the reasons why women were not fully adherent to their medication on their prior regimen (ie, took <100% of medication in the past 6 months), the reasons most often stated were “had a change in daily routine” (12%), “simply forgot” (11%), “fell asleep or slept through dose time” (10%), and “did not feel like taking any pills” (8%) (Table 4). The percentages decreased for almost all reasons after switching to the single-tablet regimen, and the decrease was greatest for the reasons, “had a change in daily routine” (from 12%–6%, P = 0.04) and “did not feel like taking any pills” (from 8%–2%, P = 0.01).
In this treatment-experienced population of HIV-infected women in the United States, we found that single-tablet regimen use was associated with significant improvements in adherence and virologic suppression. We also found suggestive evidence that it may also improve overall QOL and reduce the incidence of clinical events such as AIDS-defining illness and death. These associations were consistent based on 2 complementary approaches: a nested cohort study that compared periods of single-tablet ART use with periods of multiple-tablet ART use among similar individuals, and a case-crossover study that limited assessment to women who recently switched regimens. Our approach allowed us to make generalizations about the effectiveness of single-tablet regimen use in real-world conditions that are not restricted to those found in clinical trials.
Our results are broadly consistent with those reported in the literature,15,17,38 extending these findings to women who often have characteristics predisposing them to lower adherence to HIV treatments. The levels of adherence among women that we observed are consistent with other recent studies in the United States6,7 and add to an accruing body of evidence supporting benefits of regimen simplification.8,9,39 Our demonstration of improved virologic suppression as a consequence of single-tablet regimen use provides a partial explanation for published secular improvements in suppression among HIV-infected individuals over time.40 However, the magnitude of the increases attributable to single-tablet regimens (5%–18%) during the study period suggests that these regimens provide only incremental improvements on treatment outcomes in our population. Other factors, such as improved retention in care, may also contribute to these increases and are the focus of interventional studies.41,42
Use of single-tablet formulations reached only about 20% of this group through 2013, which is lower than previously reported in some other settings.8 This level may reflect the clinical history of this treatment-experienced cohort, with some women having been enrolled in the study for up to 19 years. Switching to a single-tablet regimen may not have been considered a priority to their providers if they were already stable on their current regimen, if they already developed resistance to one of the components of the available single-tablet regimens, or if they were planning to become pregnant. In contrast, the few women who were ART-naive before initiating therapy during the study period started on a single-tablet regimen 48% of the time.
Continued monitoring of the effects of emerging adherence strategies is warranted to strengthen the evidence base, especially as the health care environment continues to evolve in the United States and internationally. For example, it has been postulated that as generic versions of individual components of single-tablet regimens become available, some individuals may switch back to multiple-tablet formulations due to their anticipated lower cost, particularly in resource-poor settings.43 The potential effects of such a change on adherence outcomes in our population will be important to follow over time. Future work should also follow the outcomes of previously ART-naive women initiating single-tablet regimens, including younger women currently being recruited to join the WIHS as new participants.
Our study has limitations. One limitation is that ART adherence is based on self-report rather than medication event monitoring systems or unannounced pill counts.17 However, self-report has been shown to have comparable validity with other more expensive monitoring systems44,45 and is recommended for routine adherence monitoring in patients despite the potential for reporting bias.46 Other limitations relate to our measurement of adherence. Assessing adherence at 6-month intervals only captures behaviors only in a broad sense. Use of 95% adherence as the outcome of interest, which is based on older studies of unboosted PIs,27 may be too conservative for more recent regimens that may not require levels of adherence as high47 and therefore may mask additional benefits of single-tablet regimens. Despite these drawbacks, the uniformity and regularity of adherence assessment over the 8-year study period improves the robustness of our findings. We grouped all multiple-tablet regimens together to compare these collectively with single-tablet regimens, but this makes it difficult to distinguish between benefits derived from the dosing schedule versus the regimen components.46 Finally, it is possible that the switching effects that we found in the case-crossover study are a transient consequence of counseling, and future work should also examine the sustainability of these improvements.
Despite these limitations, our study has several strengths. We report trends in single-tablet regimen use and extend known inferences on their effectiveness to HIV-infected women in the United States, a growing population with less available research addressing their unique circumstances. Our data come from a well-established prospective study population that is demographically representative of the national female HIV-infected population. The WIHS's detailed longitudinal data on health behaviors, medical history, and medication use were instrumental in being able to create balanced groups to minimize the possibility of confounding by indication (although residual confounding remains possible). Finally, the WIHS follows many women who either continue to participate in the study past childbearing age or have undergone sterilization procedures, and therefore it is particularly suitable to examine single-tablet regimen use among such women who can safely be prescribed EFV despite its contraindications in terms of teratogenicity.
Adherence has been described as “a set of interacting behaviors informed by individual, social, and environmental forces”.48 Our study found that about 85% of ART-treated women in the WIHS in 2013 were adherent at the 95% level, but only 50% were adherent at the 100% level, even with the availability of single-tablet regimens. Thus, the “overlapping, combination approaches” to HIV prevention advocated by the US National HIV/AIDS Strategy also apply to adherence.49 Some examples of additional evidence-based approaches that may be relevant to our study population include those that involve self-management tools and individual- and group-level education and counseling.46 Although the simplification of treatment regimens has contributed to improved adherence and virologic suppression in women, it is just 1 component of a multifaceted strategy to be able to truly maximize the therapeutic benefits of ART.
The authors would like to thank X. Xue, PhD, for statistical advice and the WIHS participants for their time and commitment. Data in this manuscript were collected by the WIHS Collaborative Study Group with centers (Principal Investigators) at New York City/Bronx Consortium (K. Anastos); Brooklyn, NY (H. Minkoff); Washington, DC, Metropolitan Consortium (M. Young); The Connie Wofsy Study Consortium of Northern California (R. Greenblatt); Los Angeles County/Southern California Consortium (A. Levine); Chicago Consortium (M. Cohen); Data Coordinating Center (S. Gange).
The WIHS Collaborative Study Group
New York City/Bronx Consortium: Montefiore Medical Center (K. Anastos, MD, Principal Investigator; A. Cajigas, MD; E. Robison, PhD; and R. Wright, MD); University of California Davis (H. Burger, MD, PhD; and B. Weiser, MD); Albert Einstein College of Medicine (R. Kaplan, PhD; and M. Keller, MD); Weill Medical College of Cornell University (M. Glesby, MD); Rutgers (D. Hoover, PhD); and Community Advisor (N. Ramos-Santiago).
Brooklyn, NY: State University of New York Health Science Center at Brooklyn (H. Minkoff, MD, Principal Investigator; D. Gustafson, PhD, Co-Principal Investigator; M. Augenbraun, MD; H. Crystal, MD; J. DeHovitz, MD, MPH; H. Durkin, PhD; S. Holman, RN, MS; J. Lazar, MD; M. Nowakowski, PhD; R. Schwartz, PhD; D. Seifer, MD; A. Sharma, MD, MS; and T. Wilson, PhD).
Washington, DC, Metropolitan Consortium: Georgetown University Medical Center (M. Young, MD, Principal Investigator; and L. Goparaju, PhD); George Washington University Medical Center (S. Silver, DA); Whitman-Walker Clinic (K. Sathasivam, MD); Montgomery County Health Department (C. Jordan, RN, MPH); Inova Health System of Northern Virginia (D. Wheeler, MD; and B. Lawrence, BS); and Community Advisors (K. Kelsey and K. Moore).
The Connie Wofsy Study Consortium of Northern California: University of California, San Francisco (R. Greenblatt, MD, Principal Investigator; P. Bacchetti, PhD; D. Cohan, MD, MPH; N. Hessol, MSPH; P. Tien, MD); Alameda County Medical Center (H. Edelstein, MD); and Alta Bates Medical Center (C. Borkert, MD); Community Advisor (N. Rodriguez).
Los Angeles County/Southern California Consortium: Keck School of Medicine, University of Southern California and Los Angeles County and USC Medical Center (A. M. Levine, MD, Principal Investigator; Y. Barranday, BA; M. Nowicki, PhD; L. Pearce, PhD; J. Richardson, DrPH); the Santa Barbara County Department of Health Services (E. Downing, MD); University of Hawaii (C. Shikuma, MD); and Community Advisor (E. Sanchez).
Chicago Consortium: Cook County Hospital (M. H. Cohen, MD, Principal Investigator; A. French, MD; K. M. Weber, BSN); University of Illinois at Chicago (R. Hershow, MD); Rush Presbyterian-St. Luke's Medical Center (B. Sha, MD); Northwestern Memorial Hospital (S. Cohn, MD); and Community Advisor (M. Santiago).
Data Coordinating Center: Johns Hopkins Bloomberg School of Public Health (S. Gange, PhD, Principal Investigator; E. Golub, PhD, MPH, Co-Principal Investigator; A. Abraham, PhD; C. Alden, BA; K. Althoff, PhD, MPH; L. Benning, MS; C. Cox, PhD; G. D'Souza, PhD; L. Jacobson, ScD; B. Lau, PhD; S. Modur, PhD; A. Muñoz, PhD; C. Pierce, MHS; A. Platt, BS; M. Schneider, MS; E. Seaberg, PhD, MPH; G. Springer, MLA; S. Su, ScD; E. Wentz, MA; W. Yoo, BS; and J. Zhang, MS).
National Institute of Health: National Institute of Allergy and Infectious Diseases (G. Sharp, DrPH; C. Williams, PhD); Eunice Kennedy Shriver National Institute of Child Health and Human Development (K. Ryan, PhD; H. Watts, MD); National Institute of Drug Abuse (K. Davenny, MPH; R. Jenkins, PhD); and National Cancer Institute (G. Dominguez, PhD).
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