Modern highly active antiretroviral therapy (HAART) suppresses HIV-1 RNA plasma viral load (hereafter referred to as pVL) below detectable limits for long periods, enabling immune reconstitution, reducing HIV drug resistance, and preventing clinical disease progression.1-5 However, the success of HAART has been accompanied by important challenges with long-term high adherence to HAART being the major determinant of therapy success.1-5
It is well recognized that high levels of adherence are necessary for achieving viral suppression (ie, less than 50 copies/mL). The adherence level may vary among the various antiretroviral drug classes, but most studies have concluded that adherence levels in excess of 95% are necessary for achieving an optimal virologic response during the first year of therapy and avert disease progression.2,3,6,7 Maintaining such high levels of adherence over, potentially, decades of treatment may represent a burden for some individuals.
Untreated HIV is associated with very high rates of viral replication and viral evolution. Theoretical models and subsequent empiric data demonstrated that complete (or near complete) suppression of HIV replication is generally achieved with regimens containing three potent antiretroviral drugs and near perfect adherence.8-10 Once effective therapy is initiated, the total body burden of replication of competent virus declines, at least during the first few years of therapy.11,12 This latter observation suggests that the level of drug exposure necessary to maintain viral suppression may be lower than the level necessary to achieve an initial virologic response, which has been shown to be true in a recent small cohort study and in previous induction maintenance studies.13-16 Based in part on these theoretical considerations, the objective of this study is to model the effect of adherence and duration of viral suppression on the risk of viral rebound in a large cohort of treatment-naïve individuals starting HAART in British Columbia (BC), Canada. We hypothesize that the level of adherence required to prevent viral rebound declines with the duration of continuous viral suppression.
This study was conducted using retrospective data from the BC Centre for Excellence in HIV/AIDS registry database, which is the only distribution source of antiretroviral agents, at no cost, to all clinically eligible HIV-infected individuals in BC.2,3 Through its HIV/AIDS Drug Treatment program established in 1992, antiretrovirals are distributed based on guidelines generated by the Centre's therapeutic committee and in accordance with the latest guidelines of use of antiretrovirals for adults and adolescents published by the International AIDS Society-USA.1 Typically, patients are monitored by physicians at intervals no longer than 3 months, and their prescriptions are renewed or modified and their addresses are updated. To maintain the profile of Drug Treatment program patients up to date, the consent form signed by these individuals at the time of enrolment allows us to conduct regular linkages with a number of provincial administrative databases to obtain their current information regarding mortality and morbidity. Deaths are identified on a continuous basis from physician reports and through record linkages carried out with the BC Division of Vital Statistics. Morbidity information is obtained from linkages with administrative databases containing hospital discharge data, emergency admissions, medical visits, and laboratory testing.
Eligible study participants were 18 years old or older, naïve to antiretroviral therapy when they started a regimen consisting of two nucleoside/nucleotide analogs plus either 1) a nonnucleoside reverse transcriptase inhibitor (NNRTI); or 2) a protease inhibitor boosted with 400 mg/day or less ritonavir (boosted PI); or 3) a single protease inhibitor (nonboosted PI). In this study, we decided to use an intention-to-treat approach and to not update changes in treatment over time. These individuals have started HAART between January 1, 2000, and June 30, 2006, and were followed until June 30, 2007, and they were included if they had at least one baseline CD4 cell count and a pVL measurement available within 6 months before the first antiretroviral starting date. The data were adjusted for 1) scheduled treatment interruptions, given that information on the return date of the individual to the program is unclear; 2) individuals moving out of the province; 3) deaths from non-AIDS or AIDS-related causes; 4) lost to follow-up; and 5) individuals enrolled in a blinded trial involving receiving placebo medication. In these situations, we opted to censor an individual at the last contact date before each of these events. This analysis has received ethical approval from the University of British Columbia Ethics Review Committee at the St Paul's Hospital site.
The Centre's guidelines recommend that pVL and CD4 cell count be monitored at baseline, at 4 weeks after starting antiretroviral therapy, and every 3 months thereafter. The Roche Amplicor Monitor ultrasensitive assay version 1.5TM (Roche Diagnostics, Laval, Quebec, Canada) was used to measure pVL centrally at the St Paul's Hospital virology laboratory in BC with the lower and upper limits of quantification ranging from 50 to 100,000 copies/mL. CD4 cell counts were measured by flow cytometry followed by fluorescent monoclonal antibody analysis (Beckman Coulter, Inc, Mississauga, Ontario, Canada). HIV drug resistance genotyping was performed centrally at the Centre's laboratory on samples with pVL 250 copies/mL or greater collected at baseline and after HAART initiation. Samples were assigned to one of four resistance categories based on a modification of the IAS-USA table.17 Samples were considered resistant if they displayed one or more major resistance mutations in any of the four categories: 1) lamivudine/emtricitabine (184I/V); 2) any other nucleoside reverse transcriptase inhibitors (41L, 62V, 65R, 67N, 69D or insertion, 70R, 74V, 75I, 151M, 210W, 215F/Y, or 219E/Q); 3) any NNRTIs (100I, 103N, 106A/M, 108I, 181C/I, 188C/H/L, 190A/S, P225H, M230L or 236L); and 4) any PIs (30N, 46I/L, 48V, 50L/V, 54V/L/M, 82A/F/S/T, 84V, or 90M). Lamivudine/emtricitabine resistance was considered as a separate resistance category as a result of its high frequency and the lack of crossresistance conferred to other nucleoside reverse transcriptase inhibitors.
The main outcome was viral rebound defined as the first of at least two consecutive pVLs greater than 400 copies/mL after initial viral suppression (ie, first of at least two consecutive pVL less than 50 copies/mL) (coded as yes versus no).
The main exposures in this analysis were longitudinal adherence level, percentage of follow-up time with pVL less than 50 copies/mL, and presence of drug resistance in any of the four resistance categories before rebound or censoring date. To calculate the percentage of follow-up time with pVL less than 50 copies/mL, we were required to also obtain pVL measurements longitudinally, ie, every 3 months, from the date of first suppression (time zero) until the viral rebound or censoring date of the study. Longitudinal adherence levels were synchronized with the dates of the pVL measurements. Adherence level, for each period, was defined as the number of days of antiretroviral drugs dispensed divided by the number of days of follow-up (expressed as percent). Estimates of adherence to antiretroviral therapy were based on the different regimen exposures for each patient. Although patients with undetectable pVL less commonly have medications changed, the regimens can change as a result of adverse effects or other medical and nonmedical reasons, and we also accounted for those changes. Measuring adherence to any specific antiretroviral drug as index medication when it can be changed at any point in time makes it difficult for accurate monitoring. For this reason, the measure of adherence that we chose to adopt does not use any specific index medication, and it only measures the overall exposure to any antiretroviral regimen. For descriptive purposes, we also presented information on adherence during the first year of therapy; however, this measure of adherence was not included in any of the statistical analysis. For the longitudinal analysis, we categorized adherence into four groups: 0% to less than 40%, 40% to less than 80%, 80% to less than 95%, and 95% or greater. These bounds have been previously shown to be important in explaining antiretroviral drug resistance, immunologic, and virologic outcomes.2,18 The other explanatory variables investigated were measured at the time of HAART initiation, and they included age, gender, pVL (log10 transformed), AIDS diagnosis, history of injection drug use (IDU), and year of first therapy. Nadir CD4 cell count was also considered in the model and defined as the lowest CD4 for a person before receiving therapy and until the time of first suppression. Note that nadir CD4 cell count was based on CD4 cell count data available in our database, which captures 90% of all CD4 tests done in the province. HAART regimens were classified at the time of first suppression (NNRTI, boosted or multiple PIs, and other antiretroviral combinations). In sensitivity analyses, we investigated whether therapy switches influenced the odds of viral rebound among those who rebounded and those who were suppressed until the end of follow-up. The allowable switches were NNRTI ↔ unboosted PI, NNRTI ↔ boosted PI, NNRTI ↔ multiple PI, unboosted PI↔ boosted PI, unboosted PI ↔ multiple PI, and boosted PI ↔ multiple PI.
To analyze the longitudinal effect of the main exposures and the previous explanatory variables on the odds of viral rebound, we built explanatory models using Generalized Estimating Equations assuming a binomial distribution, a logit link function, and an autoregressive correlation structure of order 1.19 A backward stepwise technique was used in the selection of covariates for an explanatory model.18 The selection of variables was based on two criteria: Akaike Information Criterion (AIC) and Type III P values. These two criteria balance the model choice on finding the best explanatory model (Type III P values; lower P values indicate more significance) and at the same time a model with the best goodness-of-fit statistic (AIC; lower values indicate better fit). At each step of this process, the AIC value and the Type III P values of each variable are recorded, and the variable with the highest Type III P value is dropped until there are no more variables left. The final model has the lowest AIC. Categorical variables were compared using the chi-square or Fisher exact test, and continuous variables were compared using the Wilcoxon rank-sum test. All analyses were performed using SAS software Version 9.1.3 Service Pack 3 (SAS, Cary, NC).
Overall Cohort Characteristics
A total of 1305 antiretroviral-naïve adults (84% males) were eligible to participate in this study. At baseline, the median age was 42 years (interquartile range [IQR], 36 to 49 years), the median CD4 cell count nadir was 130 cells/mm3 (IQR, 50 to 200 cells/mm3), the median pVL was 5.0 log10 copies/mL (IQR, 4.7 to 5.0 log10 copies/mL), and 22% of individuals had a history of IDU. At the time of suppression, 543 (41%) individuals have not been tested for resistance, mainly as a result of the fact that their viral loads were less than 250 copies/mL and, therefore, genotypic testing could not be performed.
As of June 30, 2007, 8.4% of individuals died of non-AIDS or AIDS-related causes (rate 17.0 per 1000 person-years), 3.8% were lost to follow-up (rate 9.9 per 1000 person-years), 1.8% moved out of BC (rate 4.6 per 1000 person-years), 0.1% censored because they have enrolled in a blinded trial involving receiving placebo medication (rate 0.2 per 1000 person-years), and 88.0% were followed until the study ending date (rate 232.0 per 1000 person-years).
Risk of Viral Rebound
Of the 1305 individuals who achieved an initial virologic response, 274 (21%) subsequently experienced viral rebound. The median time of suppression before rebound in these 274 individuals was 2.0 years (IQR, 1.1 to 3.5 years). Viral rebound after suppression was independently associated with being female, having a history of IDU, starting HAART in 2000 to 2001 (as compared with after 2001), receiving a treatment regimen that did not include an NNRTI or a boosted PI, being younger, and having resistance to any class of antiretrovirals (P < 0.01) (Table 1). In total, 239 (23%) of individuals who did not experience a viral rebound changed therapy during the time they were suppressed, and 67 (24%) individuals changed therapy in the group that rebounded. These percentages were not statistically different (P = 0.51).
The duration of prior viral suppression was also predictive of subsequent rebound risk. Viral rebound was less likely to occur among those with long duration of suppression (in years) (odds ratio [OR], 0.37; 95% confidence interval [CI], 0.32 to 0.42). This translates into an odds of viral rebound decrease of 8% per month of continuous viral suppression across all adherence levels. For individuals with high levels of adherence (95% or greater), the probability of rebound was 0.10 (IQR, 0.07 to 0.40) after being suppressed for 12 months and 0.04 (IQR, 0.02 to 0.06) after being suppressed for 72 months. Among individuals with moderate levels of adherence (80% to less than 95%), the probability of rebound was 0.85 (IQR, 0.16 to 0.94) after being suppressed for 12 months and 0.08 (IQR, 0.03 to 0.21) after being suppressed for 72 months. Among individuals with low adherence (less than 40%), the probability of rebound was 0.68 (IQR, 0.29 to 0.85) after being suppressed for 12 months and 0.05 (IQR, 0.03 to 0.10) after 72 months (Fig. 1). In this analysis, therapy switches between the time of first suppression and the end of follow-up did not play a role in the individual's probability of viral rebound.
The level of adherence was also a consistent factor explaining the outcome once viral suppression was achieved. After adjusting for duration of suppression, individuals with adherence less than 95% were 11% more likely to rebound (less than 40%: OR, 1.16; 95% CI, 1.12 to 1.21; 40% to less than 80%: OR, 1.07; 95% CI, 1.05 to 1.10; and 80% to less than 95%: OR, 1.09; 95% CI, 1.03 to 1.14) than those 95% or greater adherent. Individuals with drug resistance before achieving viral rebound were 2.78 (95% CI, 1.68 to 4.59) times more likely to experience viral rebound than those with no resistance; in addition, individuals not tested, mostly often because their viral loads were less than 250 copies/mL, were at lower risk to rebound (OR, 0.61; 95% CI, 0.39 to 0.94) (Table 1).
It is well known that high levels of adherence are necessary to achieve an initial viral response. The degree to which high levels of adherence are needed to maintain viral suppression, once achieved, has not been previously well defined. In our cohort of over 1000 well-characterized individuals receiving their initial HAART regimen, we found that once viral suppression was initially achieved, high levels of adherence (95% or greater) were still needed for at least the first year. Over time, however, the risk of viral rebound strongly decreased with maintained viral suppression irrespective of the level of adherence.
Our data are consistent with recent findings by Rosenblum et al who also found that the risk of viral rebound declined over time in a smaller, far more heterogeneous group of marginally housed highly treatment-experienced individuals followed in San Francisco.13 In that cohort, the risk of virologic failure for adherence between 75% and less than 90% was 0.34 after 1 month of suppression and 0.06 after 12 months of suppression. Our findings are also consistent with induction maintenance studies and lopinavir-ritonavir monotherapy studies that suggest lower levels of antiretroviral drug exposure are required to sustain viral suppression once viral suppression is achieved than when initiating therapy with high-level viremia.14-16 These data suggest that individuals are most vulnerable to missed doses shortly after achieving viral suppression and may be able to better tolerate missed doses with long-term viral suppression.
One possible explanation for our finding is that lower levels of drug exposure are required to prevent viral rebound because the overall viral burden declines over time. This was perhaps most clearly shown by Palmer and colleagues,12 who used a novel real-time reverse transcriptase-initiated polymerase chain reaction assay with single-copy sensitivity to quantify the level of viremia in long-term PI-treated individuals. The level of residual viremia, which the authors assumed was coming from a long-lived cellular reservoir rather than active replication, declined during the first 9 to 15 months of therapy and then reached a stable level. These data are generally consistent with a number of other observations using different assays.11,20-23
Another possible explanation for our findings is survivor bias. This bias may be entirely responsible for the observed decreases in probability of viral rebound with longer suppression. Specifically, the subpopulation of individuals who remain virally suppressed for longer periods may differ in many important ways from the rest of the enrolled cohort. We, therefore, cannot infer any cause-effect relationship between duration of suppression and lower probability of viral rebound. To address this issue, we conducted several subanalyses to determine if this effect holds after stratifying for pre-HAART factors such as CD4 cell count, history of IDU, and sex and for post-HAART factors such as regimen type, adherence, and duration of viral suppression. Note that the list of possible covariates used in these subanalyses is not exhaustive, and we acknowledge that there are several other possible factors, not available in our data, that we could have stratified the data by. Overall, we observed that in our multivariate analyses, adjusting for both baseline and time-dependent factors, duration of viral suppression was still highly associated to subsequent rebound risk with those individuals with longer duration of suppression having a lower risk of subsequent viral rebound. There were subtle differences depending on how we stratified the data, but the message in all subanalyses was that the “cost” of missed doses declines the longer an individual is suppressed. Although this phenomenon is observed throughout many clinical practices, it is still not clear what mechanism (eg, reservoir size, genetic factors, selection bias) explains our findings. Because of these limitations, it is important to reinforce the message to individuals that sustained and near perfect adherence increases the probability of long-term viral suppression.
There are several novel aspects to this study. Our cohort had a median duration of follow-up after achieving suppression of 4 years (minimum, 0.2 years, maximum, 7.2 years), included individuals initiating therapy receiving the three most common classes of antiretrovirals, and offered comprehensive adherence information. Additionally, our study was carried out within a provincewide treatment program providing free access to medical attention, combination antiretroviral therapy, and laboratory monitoring. We are confident, therefore, that our results were not highly influenced by access to therapy, a factor that has often compromised the interpretation of other cohort studies.
There are several potential limitations in our study. First, we used time-updated pharmacy-refill compliance to therapy as a surrogate for adherence. This is a conservative measure of adherence that likely overestimates the true level of adherence. It is important to mention that there is no gold standard to measure adherence, and given that our data were obtained from a registry of all patients with HIV who have ever received therapy in BC, this measure of adherence was chosen as the most appropriate and effective method to assess adherence in our setting. Second, although we showed that having resistance to any class before suppression did not affect the risk of rebound, we cannot discard the possibility of measurement bias given that 40% of our study participants lacked prior resistance data. Third, we used an intention-to-treat approach and did not update changes in treatment over time in the main analyses. However, our sensitivity analyses indicated that therapy switches did not affect the risk of viral rebound.
In summary, our results demonstrate that duration of continuous viral suppression under HAART had a strong effect in preventing viral rebound regardless of the adherence level. Our results reinforce the message to individuals that sustained and near perfect adherence increase the probability of long-term viral suppression, particularly critical at the earliest stages of treatment; however, because the resilience of HAART increases over time, it is possible that individuals remain fully suppressed even after missing some doses of medication. Therefore, we call for a multidisciplinary long-term comparative study of early failures versus sustained suppressors as one of the ways to better understand the factors associated with the phenomenon observed in this study.
We thank the staff from the British Columbia Centre for Excellence in HIV/AIDS for their assistance and commitment to maintain a state-of-the-art database and our patients for participating in our study.
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