Overall, 134 individuals reported differential adherence on more than one occasion (Table 1 and Fig. 1). This represented 10% of the overall population, and 33% of those individuals reporting differential adherence at any point during the study. By randomized strategy, reporting differential adherence on more than one occasion was more common in participants randomly assigned to the NNRTI (12%) and three-class (11%) strategies than the PI strategy (6%; P = 0.007). The maximum number of times that differential adherence was reported was 13 times (72% of follow-up visits for that individual) by a participant randomly assigned to the NNRTI strategy.
Characteristics at baseline for participants who reported differential adherence at least once during follow-up and for those who never reported differential adherence are presented in Table 2. The median age of the overall population was 38 years; 17% were Latino; 54% were black; 21% were women; 61% were men reporting a history of sex with other men; 15% reported a history of injection drug use; and 38% reported an AIDS diagnosis before study enrollment. The median baseline CD4 lymphocyte count was 163 cells/μl and the median baseline HIV-RNA level was 5.1 log10 copies/ml. In multivariate logistic regression models, no baseline demographic or disease-specific factors were significant predictors of differential adherence during follow-up (data not shown).
Of the 403 individuals with differential adherence, 146 (36%) reported it before initial virological failure and 71 (18%) had antiretroviral resistance detected at the time of initial virological failure. A summary of the multivariate Cox proportional hazards regression analyses is presented in Table 3. For the overall cohort, differential adherence before initial virological failure was associated with an increased risk of initial virological failure compared with those with no differential adherence (HR 1.33, 95% CI 1.10–1.60). Similarly, participants reporting differential adherence before initial virological failure had an increased risk of initial virological failure with antiretroviral resistance (HR 1.34, 95% CI 1.03–1.75) compared with those without differential adherence. By randomized strategy, differential adherence significantly increased the risk of initial virological failure (HR 1.63, 95% CI 1.22–2.19) and initial virological failure with antiretroviral resistance (HR 1.75, 95% CI 1.16–2.64) in the three-class strategy but not in the PI or NNRTI strategies.
Other factors significantly associated with time to initial virological failure in the multivariate model for the overall cohort included mean cumulative adherence (HR 1.24 per 10% decrease), age (HR 0.82, per 10-year increase), black race (HR 1.79 compared with white or other individuals), baseline CD4 lymphocyte count (HR 0.95 per 100 cell increase), baseline log10 HIV-RNA (HR 1.37 per log10 increase), and not being on antiretroviral medications (HR 3.56 compared with those on antiretroviral medications; Table 3). These same factors, except for not being on antiretroviral medications, were significantly associated with time to initial virological failure with antiretroviral resistance (Table 3).
The overall cohort was used to explore a potential ‘dose effect’ for differential adherence using Cox regression models adjusted for the same baseline and time-updated covariates as in Table 3. Compared with participants not reporting any differential adherence, those reporting differential adherence only once before initial virological failure had a significantly increased risk of initial virological failure (HR 1.28, 95% CI 1.04–1.57), whereas those reporting differential adherence more than once had an even greater risk (HR 1.54, 95% CI 1.08–2.20; Fig. 2). Similarly, compared with participants without differential adherence, those who reported differential adherence only once had an increased risk of initial virological failure with antiretroviral resistance (HR 1.22, 95% CI 0.91–1.64), although this finding was not statistically significant. Participants who reported differential adherence more than once had twice the risk of initial virological failure with resistance compared with those without differential adherence (HR 1.93, 95% CI 1.19–3.15).
In adjusted Cox regression models, differential adherence was not associated with the composite endpoint of progression of HIV disease to AIDS or death (HR 1.17, 95% CI 0.86–1.58). Similarly, differential adherence was not associated with the time to first CD4 lymphocyte count of less than 200 cells/μl among the 618 participants with baseline CD4 lymphocyte counts of 200 cells/μl or greater (HR 0.98, 95% CI 0.60–1.60).
Differential adherence was commonly reported in this randomized clinical trial of alternative initial ART strategies; 29% of participants self-reported differential adherence on at least one occasion. Neither demographic nor baseline clinical data were predictive of differential adherence. Although differential adherence was common in each randomized strategy, participants randomly assigned to the three-class strategy were more likely to report this behavior. Self-reported differential adherence was independently associated with an increased risk of initial virological failure and initial virological failure with antiretroviral resistance after adjusting for cumulative adherence and other potential confounders. An association between differential adherence and clinical or immunological outcomes was not evident.
In clinical practice, it is not uncommon for individuals to report different levels of adherence to antiretroviral regimen components. Whereas adherence to ART has been extensively studied, the pattern of differential adherence has not been thoroughly evaluated. Two small studies suggested that different levels of adherence to regimen components was uncommon [14,15]. A third study using pharmacy refill adherence data found that 15% of unselected patients in a clinic cohort exhibited differential adherence during a median follow-up of 2.5 years, and that differential adherence during an initial antiretroviral regimen increased the risk of adverse clinical outcomes .
The current study expands the differential adherence literature in several ways. First, it confirms that differential adherence is common. This has previously been shown in an unselected clinic population and now in a broad population of US clinical trial participants, two distinct populations . Second, despite uncertainty in the best way to assess differential adherence, self-reported adherence appears to be an effective measurement tool. Self-reported adherence assessments, like the CPCRA 7-day recall used in this study, are widely available and inexpensive to implement in clinical and research settings. Furthermore, they can assess adherence to all components of a regimen, which has generally not been the case in studies using microelectronic monitoring systems. Third, our study validates the clinical relevance of differential adherence by showing its relationship to the biologically plausible outcomes of virological failure and virological failure with antiretroviral resistance. The lack of an association between differential adherence and clinical outcomes in a treatment-naive population may reflect the prolonged time between virological failure and the occurrence of HIV disease progression events that is expected in this group .
A common theme in the antiretroviral adherence literature has been to analyse baseline factors that might predict non-adherence to ART [17–19]. In this report we have taken an initial look at potential predictors of differential adherence to ART. No demographic or baseline disease-specific factors appear to be associated with future report of differential adherence. Notably, we did not have information regarding active substance abuse and active mental illness at baseline, both of which have been associated with antiretroviral non-adherence in general [3,17]. The significantly higher rate of discontinuation of one or more drugs in the antiretroviral regimen because of toxicity in the three-class strategy, and the greater frequency of differential adherence among these participants, suggest that regimen complexity or tolerability may be a factor in the frequency of differential adherence . Regimen and drug-specific variables that may be risk factors for differential adherence in the FIRST study will be evaluated in subsequent on-treatment analyses.
A chief concern with differential adherence is that, in effect, individuals have periods of treatment with only one or two antiretroviral agents. It is known that mono and dual-therapy for HIV is associated with less durable virological responses and a greater incidence of antiretroviral resistance [6–8]. Therefore, we hypothesized that differential adherence and the extent of this behavior reported over time would be associated with virological failure and virological failure with antiretroviral resistance. The clear association between differential adherence and these two outcomes demonstrates that self-reported differential adherence is a clinically relevant pattern of non-adherence. The ‘dose–response’ association between differential adherence and virological failure with resistance further supports this hypothesis. Why this behavior appears more deleterious in patients randomly assigned to the three-class strategy is unknown. It may have to do with the magnitude of differential adherence or the drugs or drug classes that are less often taken.
Detailed analyses of other antiretroviral adherence patterns may prove useful, and there is ongoing research in this area [21–23]. How descriptions of patterns of non-adherence will influence future adherence research and interventions is unclear. For differential adherence, systematic interventions may be warranted because of the frequency of this behavior and the lack of demographic or clinical factors to predict its occurrence. Many current successful adherence intervention strategies rely on behavioral modification [20,24]. For differential adherence it may be possible to develop a healthcare system-level intervention. The development and usage of new fixed-dose combination dosage forms containing all regimen components would make differential adherence impossible. Requiring all regimen components to be refilled in sync, with intervention targeting individuals not requesting refills of all regimen components, may also be of benefit. Differential adherence exerts an independent effect on virological outcomes, and therefore future adherence intervention research may need to address both differential adherence and overall non-adherence.
A limitation of this analysis, the lack of an on-treatment assessment, will be addressed in future analyses of this study population. Other important limitations of this study are presented here. First, a Likert scale does not provide the fine detail that would allow a more precise calculation of the magnitude of the difference in the level of adherence between regimen components. We were thus unable to quantify the influence of the level of differential adherence on outcomes. Second, participants in clinical trials may differ from general clinic populations in a number of ways. It is, however, notable that differential adherence has now been documented among both clinical trials participants and a general clinical cohort. Third, differential adherence is not possible with regimens composed of a single fixed-dose combination dosage form, but we were unable to assess the impact of a completely co-formulated regimen in this study. Fourth, for the virological failure with resistance endpoint, the lack of baseline resistance testing for the entire population limited our ability to assess whether resistance mutations at first failure were new. Baseline resistance tests were, however, performed on stored samples for a random subset (N = 491) of FIRST participants . Of the 306 participants with genotypic resistance tests at both baseline and virological failure, 18 (6%) had definite drug resistance at baseline. Therefore, it is likely that most of the resistance documented at the time of virological failure among patients in this study was acquired resistance. Finally, previous reports suggest that self-reported adherence overestimates true adherence behavior.
In summary, differential adherence was common among patients starting combination ART and was associated with the clinically relevant outcomes of virological failure and failure with drug resistance. Over longer periods of time this detrimental effect of differential adherence on virological outcomes is likely to translate into worse clinical outcomes, although this remains to be proven. Further research will be required to evaluate interventions to decrease differential adherence.
The authors would like to acknowledge and thank the participants in the FIRST study and the dedicated staff at participating CPCRA units.
This study was presented in part at the 2nd International Conference on HIV Treatment Adherence, Jersey City, New Jersey, USA, 28–30 March 2007.
Sponsorship: The National Institute of Allergy and Infectious Diseases, National Institutes of Health grants 5U01AI042170, 5U01AI046362 and 1U01AI068641 provided financial support for this work as part of the FIRST study (CPCRA 058) and INSIGHT Network. E.M.G. is supported by a career development award from the National Institutes of Health, National Institute of Allergy and Infectious Diseases (K01 AI067063).
Conflicts of interest: None.
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Keywords:© 2008 Lippincott Williams & Wilkins, Inc.
adherence; antiretroviral resistance; differential adherence; HIV; virological failure