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The American Journal of Managed Care April 2016
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Single- Versus Multiple-Tablet HIV Regimens: Adherence and Hospitalization Risk
S. Scott Sutton, PharmD; James W. Hardin, PhD; Thomas J. Bramley, RPh, PhD; Anna O. D’Souza, BPharm, PhD; and Charles L. Bennett, MD, PhD, MPP
Assessing the Impact of an Integrated Care System on the Healthcare Expenditures of Children With Special Healthcare Needs
Mircea I. Marcu, PhD; Caprice A. Knapp, PhD; David Brown, PhD; Vanessa L. Madden, BSc; and Hua Wang, MS
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Jennifer King, PhD; Vaishali Patel, PhD; Eric Jamoom, PhD; and Catherine DesRoches, DrPH
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Bruce W. Sherman, MD; Wendy D. Lynch, PhD; and Carol Addy, MD, MMSc
Patient Safety Intervention to Reduce Unnecessary Red Blood Cell Utilization
Scott Hasler, MD; Amanda Kleeman MS; Richard Abrams, MD; Jisu Kim, MD; Manya Gupta, MD; Mary Katherine Krause, MS; and Tricia J. Johnson, PhD
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Marissa Escobar Quinones, PharmD, CDE; Margaret Youngmi Pio, PharmD, BCPS, CDE; Diem Hong Chow, PharmD, CDE; Elizabeth Moss, PharmD, CDE, BCACP; Jeffrey Lynn Hulstein, PharmD, CDE; Steven Micheal Bo
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Todd H. Wagner, PhD; Rachel Willard-Grace, MPH; Ellen Chen, MD; Thomas Bodenheimer, MD, MPH; and David H. Thom, MD, PhD, MPH
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Peter Cunningham, PhD

Single- Versus Multiple-Tablet HIV Regimens: Adherence and Hospitalization Risk

S. Scott Sutton, PharmD; James W. Hardin, PhD; Thomas J. Bramley, RPh, PhD; Anna O. D’Souza, BPharm, PhD; and Charles L. Bennett, MD, PhD, MPP
Single-tablet regimens are associated with higher adherence rates, decreased hospitalizations, and a higher proportion of patients with undetectable viral load compared with multiple-tablet regimens in patients with HIV/AIDS.
As shown in Figure 1, at a threshold of 95%, a significantly higher proportion of STR versus MTR patients were adherent (75% vs 55.7%; P <.001). Similar results were noted using the ≥80% threshold (STR vs MTR: 90% vs 77.5%; P <.001). After adjusting for baseline covariates, patients in the STR cohort had almost 2 times the odds of being adherent (MPR ≥95%), as shown in Table 2 (odds ratio [OR], 1.98; 95% CI, 1.81-2.17; P <.0001). All other covariates included in the model significantly predicted adherence except for the CCI score. Of note, viral load at baseline was a significant predictor of adherence, and its exclusion did not affect the magnitude or direction of the main predictor (regimen type); hence, final results of the model include viral load at baseline. Adherence defined as MPR ≥80% demonstrated similar results (data not shown); the odds of adherence were slightly more than 2 times higher with the STR versus MTR group (OR, 2.16; 95% CI, 1.92-2.43; P <.001).

Clinical Outcomes

Less than one-third (29.5%) of the study sample had a hospitalization after the index date. Compared with patients receiving an MTR, a lower proportion of patients receiving an STR had hospitalizations (26.8% vs 31.3%; P <.001). In addition, the average number of hospitalizations per patient was lower (2.2 vs 2.7; P <.001) and the number of days from index date to hospital admission was longer (376 vs 345 days; P <.001). After adjusting for covariates, STR patients had 31% lower odds of experiencing a hospitalization during follow-up (hazard ratio [HR], 0.69; 95% CI, 0.64-0.74; P <.001) (Figure 2). The number of hospitalizations was also significantly lower for the STR compared with the MTR cohort, with STR patients having 44% fewer hospitalizations compared with MTR patients (incidence rate ratio, 0.56; 95% CI, 0.53-0.58; P <.001). Similar to the adherence model, viral load was a significant predictor of future hospitalization risk, and its exclusion did not affect the impact of type of regimen (HR, 0.67; 95% CI, 0.62-0.72; P <.001). Therefore, the final model included viral load at baseline.

Overall, during follow-up, the proportion of patients with undetectable viral load increased to 61.3% from a baseline level of 44.6%. The improvement was noted in both cohorts, with a significantly higher number of STR patients having an undetectable viral load compared with MTR patients during follow-up (63.9% vs 59.6%; P <.001) (Figure 3). After accounting for baseline viral load detectability and other covariates, the STR cohort had 21% higher odds of having an undetectable viral load during follow-up (OR, 1.21; 95% CI, 1.11-1.32; P <.001). STR patients also had significantly lower viral load values compared with MTR patients (7376.2 vs 8673.6; P <.001).

This retrospective database analysis of US veterans compared 2 types of HAART, STR and MTR. The goal of the study was to assess the impact of pill burden on adherence, hospitalization, and viral load. This study found that patients receiving an STR had significantly better adherence than patients receiving an MTR. At MPRs of 95% and 80%, a significantly higher portion of STR patients was adherent compared with MTR patients. Furthermore, STR patients were 2 times more likely to be adherent compared with MTR patients. Patients receiving an STR also had a 31% lower risk of hospitalizations, 46% fewer hospitalizations, and 21% greater odds of undetectable viral load compared with MTR patients.

The outcomes in our study are consistent with meta-analyses conducted by Parienti et al,24 van Galen et al,25 and Nachega et al,26 and with other similar studies using claims data in other populations.15,16 Parienti and colleagues’ meta-analysis reported an improvement in adherence with a once-daily regimen compared with a twice-daily regimen.24 Van Galen and colleagues reported a meta-analysis demonstrating that administering medications as a fixed-dose combination improved adherence compared with the same active drugs administered as separate pills; however, they also noted that there is a limited number of randomized controlled trials regarding the subject.25 Nachega and colleagues reported a meta-analysis of randomized controlled trials demonstrating that a lower pill burden was associated with better adherence and virological suppression.26 Sax and colleagues demonstrated that patients who received treatment as a single pill per day had significantly better adherence than patients who received 3 or more pills per day, and they were less likely to have a hospitalization.16

Additional studies have also demonstrated that patients who were adherent were less likely to have a hospital stay.8,15 Given our large national sample size, we feel our data are robust in evaluating the effects of pill burden on adherence and hospitalization. Additionally, this study demonstrated that the pill burden has an impact on viral load. After accounting for baseline viral load detectability and other covariates, the STR cohort had 20% higher odds of having an undetectable viral load during follow-up.

Among patients receiving complex, multi-pill regimens, adherence estimates range from 60% to 70%.4-6 Our cohort of patients receiving an MTR demonstrated that pill burden might be related to HIV clinical outcomes. Achieving optimal outcomes in HIV treatment requires a sustained level of adherence. Studies conducted on patients receiving older HAART regimens identified a necessary adherence rate of at least 95% to achieve a lower risk of virologic failure, fewer hospital days, and reduced morbidity and mortality.4,6,25 Simpler regimens with longer half-lives and pharmacokinetic enhancers are now utilized in HAART regimens; however, in our study, having an STR and ultimately, a smaller pill burden, improved adherence, decreased hospitalizations, and improved viral load in spite of longer half-lives and pharmacokinetic enhancers for MTR.

This study attempted to control for various differences in the study population and the effects these differences might have on adherence and hospitalization. Specifically, multivariate logistic regression was undertaken to control for age, race, geographic location, CCI score, mental health disorders, drug and alcohol abuse, index year, treatment-naïve status, number of pills per day, and undetectable viral load. After adjusting for the baseline covariates, patients in the STR cohort had almost 2 times the odds of being adherent and a 31% lower hazard of experiencing a hospitalization during follow-up. All other covariates included in the model significantly predicted adherence except for the CCI score.


Our study has several limitations common to observational claims database analyses. Adherence was measured from filled prescriptions; however, studies have suggested that pharmacy refill rates and MPRs are good depictions for actual medication adherence.27 Because patients were not randomized to the different treatments, we cannot exclude unmeasured confounding factors that may have influenced our outcomes. Among the most important, is that clinical trials have demonstrated that resistance or virologic failure is significantly less common in the boosted PI treatments than in NNRTI-based treatments.28,29 As such, providers may have preferentially prescribed a boosted PI to their less-adherent patients. Additionally, individualized HIV therapy can be difficult to control when evaluating antivirals. Patients may have been on an MTR because of genotypic results or salvage therapy with CCR5 antagonists. Although we attempted to control for select variables through use of multivariable models that include some of these factors, residual confounding may remain.

Adherence to ART in patients with HIV is critical for disease management, reducing morbidity and mortality, and preventing disease transmission, since poorer outcomes have been associated with nonadherence to ART. Results of our database study demonstrate that ART with an STR is associated with improved clinical outcomes, as shown by a reduced risk of hospitalizations, fewer hospitalizations, and longer time to hospitalization than ART with an MTR. Healthcare providers and payers may see a benefit in improved adherence with HAART using an STR versus an MTR based on decreased hospitalization rates and other improvements in clinical outcomes. These clinical outcomes could potentially decrease total healthcare costs in HIV patients. Future research to improve adherence, whether through drug therapy advancements through development of more STRs or other interventions, is needed.


Gilead Sciences, Inc, provided assistance with study design, data interpretation, and editing the manuscript. The University of South Carolina and William Jennings Bryan Dorn Veterans Affairs Medical Center provided assistance with data acquisition, study design, statistical analyses, data interpretation, and preparing the manuscript. Xcenda LLC provided assistance with study design, statistical analyses, data interpretation, and preparing the manuscript.

Author Affiliations: South Carolina College of Pharmacy (SSS, CLB), and School of Public Health (JWH), University of South Carolina, Columbia; William Jennings Bryan Dorn Veterans Affairs Medical Center (SSS, JWH, CLB), Columbia, SC; Xcenda, LLC (TJB, AOD), Palm Harbor, FL.

Source of Funding: This work and manuscript was supported by Gilead Sciences, Inc (PO #801021640).

Author Disclosures: Drs Sutton, Hardin, and Bennett are employees of the William Jennings Bryan Dorn Veterans Affairs Medical Center and of the University of South Carolina; the Veterans Affairs Medical Center received funding from Gilead to conduct this study and write the manuscript. Drs Bramley and D’Souza are employees of Xcenda, LLC, a consulting company that also received funding from Gilead Sciences, Inc, to conduct this study and write the manuscript. This material is the result of work supported with resources and the use of facilities at the WJB Dorn Veterans Affairs Medical Center, Columbia, South Carolina. The contents do not represent the views of the US Department of Veterans Affairs or the United States Government.

Authorship Information: Concept and design (SSS, TJB, CLB, AOD); acquisition of data (SSS, TJB); analysis and interpretation of data (SSS. JWH, TJB, AOD); drafting of the manuscript (SSS, JWH, CLB, TJB, AOD); critical revision of the manuscript for important intellectual content (SSS, JWH, CLB, TJB, AOD); statistical analysis (JWH, TJB, AOD); provision of patients or study materials (SSS); obtaining funding (SSS); administrative, technical, or logistic support (SSS, CLB); and supervision (SSS, AOD).

Address correspondence to: S. Scott Sutton, PharmD, Department of Clinical Pharmacy and Outcomes Sciences, South Carolina College of Pharmacy, University of South Carolina, 715 Sumter St (CLS 314b), Columbia, SC 29208-0001. E-mail:

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