To the Editors:
Excellent adherence to antiretroviral regimens is closely associated with achieving HIV viral suppression and preventing the development of drug-resistant virus. Missed doses, interruptions in therapy, and improper dosing can all lead to HIV drug resistance.1-3 Like many other areas of behavior change, long-term maintenance of consistent adherence has been a challenge for behavior change in the United States, and data from Africa4 indicate that adherence levels may decline over time in developing country settings as well. Reliable and valid adherence measures are essential to the study of highly active antiretroviral therapy adherence and to evaluate the impact of adherence interventions.5-9 To be useful in clinical settings, they also need to be brief and relatively simple to administer.10 Although multiple adherence measures have been found to predict viral load, there is no single gold standard for the assessment of adherence8 and most measures have been developed in the United States.11,12 In India, Shah et al13 found a cross-sectional association between past 4-day adherence and viral load in a subsample of their study in Pune and Delhi. However, no Indian studies to date have examined, in a prospective fashion, the impact of adherence on viral load, the predictive validity of combined measures, or the relationship between multiple adherence measures. This study was designed to address this gap by assessing the relationship between multiple self-reported adherence measures and HIV viral suppression in a longitudinal cohort of HIV-infected patients in Bangalore, India.
The study was conducted in the outpatient department of medicine in a Catholic hospital in Bangalore, India. Eligibility criteria included being at least 18 years old; capable of communicating in English, Kannada, Tamil, or Telugu; being HIV-infected, on antiretroviral medication for at least 1 month; and willing to participate in all follow-up visits. After referral by their physicians or our NGO collaborators, participants were brought to a private room for informed consent and an approximately 1-hour study interview. Blood was drawn at the baseline, 6-month, and 12-month visits by trained, hospital-based phlebotomists. Two hundred twenty-nine participants were enrolled in the study. The present analyses include data on those who participated in both the baseline and 12-month follow-up visits (n = 203).
The instruments were developed in English and translated into Kannada, Telugu, and Tamil. All translations were independently back-translated into English to ensure equivalence.
Adherence was assessed using five different self-report measures: 1) a modified version of the first question in the AACTG self-reported adherence instrument14 using a detailed dose-by-dose assessment of adherence in the past 4 days; 2) a calculation of the percent missed doses in the past week; 3) a calculation of the percent missed doses in the past month; and 4) a Visual Analogue Scale10 in which participants were shown a line with numbers ranging from 0 to 100 and asked to point to the place that best indicated the proportion of pills taken in the past month.
We also assessed treatment interruptions, defined as number of occasions on which the patients had missed all their medication for 2 or more consecutive days.
HIV plasma viral load tests were performed by Reliance Life Sciences laboratories (Mumbai, India) using a real-time polymerase chain reaction assay with a fluorescein-labeled Taqman probe for quantitation of HIV particles. The test was developed and its performance characteristics determined at Molecular Diagnostics and Genetics, Reliance Life Sciences. The specificity of the assay is greater than 98% and its sensitivity enables detection of 100 viral particles/mL.15
The adherence measures were treated as continuous variables to calculate Pearson correlation coefficients. All adherence rates were also dichotomized at 95% or greater to examine their relationship with viral load. Chi-square analyses were performed to assess the relationship between detectable viral load and the dichotomized adherence rate and treatment interruption variables. All statistical analyses were done using SPSS 15.0.16
At baseline, the majority of the sample reported being married (76%), male (69%), Hindu (88%), and employed (73%). Virtually all were living with their extended (52%) or “nuclear” (42%) families either in Bangalore (41%) or elsewhere in the state of Karnataka (43%). The mean age was 38 years (range, 23-74 years). Participants reported having been diagnosed with HIV for a mean of 3 years 5 months (range, 1-206 months) and taking antiretroviral medication for a mean of 21 months (range, 1-133 months). Virtually all (98%) of the participants were on an nonnucleoside reverse transcriptase inhibitor-based regimen with the most common regimens being lamivudine/stavudine/nevirapine (49%) followed by lamivudine/zidovudine/nevirapine (26%), lamivudine/zidovudine/efavirenz (8%), and lamivudine/stavudine/efavirenz (7%).
Between 83% to 92% of participants reported 95% or greater adherence during the different assessment periods. All self-reported adherence measures were significantly correlated at P < 0.001 with correlation coefficients ranging from 0.8 to 0.93. At the end of the study, half of the sample reported having experienced at least one treatment interruption of at least 48 hours in length. Twenty-eight percent of the participants had a detectable viral at that time.
As shown in Table 1, all adherence measures were significantly associated with viral suppression. We next examined whether data on treatment interruption history would improve our ability to predict viral suppression above and beyond these standard adherence measures. Only optimally (95% or greater) adherent participants (n = 169) were included in this analysis. The results showed that among optimally adherent participants, having a history of one or more treatment interruptions, were significantly associated with a lower likelihood of viral suppression than among participants who did not report any treatment interruptions (68% and 85%, respectively, P < 0.01). The inclusion of treatment interruption data correctly classified an additional 61% (23 of 38) of optimally adherent participants who presented with detectable viral load.
By 12 months, 11 participants (5%) had died and another 15 participants (6%) were lost to follow up. There were no significant baseline differences between cohort members and dropouts with regard to any of the demographic variables or adherence. However, dropouts did have a significantly lower mean baseline CD4 count than those who remained in the study (174 versus 321 cells per mm3, t = 4.65, P < 0.001).
These data show high rates of self-reported adherence during the past month, comparable to rates reported by study participants in the United States, Europe, and Africa using similar measures.9 Treatment interruptions appear to be the most common form of nonadherence in this setting. Because this behavior is typically not reported in the adherence literature, we do not know if this is comparable to behaviors in other resource-constrained settings. The self-reported adherence measures used in this study were significantly associated both with each other and with viral load, suggesting that they are indeed valid measures of pill-taking. Research settings may require multiple measures and should include viral load whenever possible. However, given that the more complex and time-consuming measures did not perform any better than the simpler ones, a brief measure such as the Visual Analog Scale may be more feasible in clinical settings.
It should be noted that these results were obtained in an urban, private, nonprofit, private setting in South India and may not generalize to other geographic regions or to public clinic settings, where the accuracy of self-report may be impacted by different factors. It should also be noted that the self-reported adherence assessments were conducted in a confidential setting, which may have increased the accuracy of self-report. Finally, the instrument was administered by highly trained study staff who were not associated with the hospital's clinic staff. Participants often report wanting to please their medical providers when asked about adherence.
The data show high rates of virologic failure in this sample despite high rates of self-reported adherence. This is similar to results reported by Shah,13 who called for the large-scale introduction of second-line therapy by the Indian government. We echo this request and note that these rates may indicate the beginning of an epidemic of drug-resistant HIV in India. More research is needed to examine this issue and to develop programs that will improve adherence, minimize treatment interruptions, and maximize the efficacy of first-line regimens, which remain the primary form of treatment in both private and public clinic settings in India.
Parts of these data were presented at the International Conference on AIDS, Mexico City, August 7, 2008, Abstract # THPE0126. The data were collected as part of a grant to the first author, #MH067513.
Maria L. Ekstrand, PhD*
Sara Chandy, MD†
Elsa Heylen, MA*
Wayne Steward, PhD, MPH*
Girija Singh, MD†
*Center for AIDS Prevention Studies, Department of Medicine, University of California, San Francisco, San Francisco, CA
†Department of Medicine, St. John's Medical College and Hospital, Bangalore, India ‡St. John's Research Institute, Bangalore, India
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