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Comparison of subjective and objective adherence measures for preexposure prophylaxis against HIV infection among serodiscordant couples in East Africa

Musinguzi, Nicholas; Muganzi, Collins D.; Boum, Yap II; Ronald, Allan; Marzinke, Mark A.; Hendrix, Craig W.; Celum, Connie; Baeten, Jared M.; Bangsberg, David R.; Haberer, Jessica E.The Partners PrEP Ancillary Adherence Study Team

doi: 10.1097/QAD.0000000000001024
Epidemiology and Social
Free

Background: Preexposure prophylaxis (PrEP) efficacy is highly dependent on adherence. Yet, it is unclear which adherence measures perform best for PrEP.

Methods: We compared three types of self-reported adherence questions (rating of ability to adhere, frequency of doses taken, percentage of doses taken) and three forms of objective adherence measurement [unannounced pill counts (UPC), electronic monitoring, plasma tenofovir levels] using data from an ancillary adherence study within a clinical trial of PrEP among East African serodiscordant couples (Partners PrEP Study). Monthly measures were assessed for the first 6 months of follow-up.

Results: One thousand, one hundred and forty-seven participants contributed 6048 person-months of data to this analysis. Median adherence was high: self-reported rating (90%), self-reported frequency (93%), and self-reported percentage (97%); UPC (99%); and electronic monitoring (97%). Prevalence of steady-state daily dosing (SSDD; ≥40 ng/ml) was 74% in a random subset of tenofovir samples obtained from 365 participants. Discrimination of SSDD versus less than SSDD levels was poor for self-reported rating [area under the receiver–operating curve (AROC) 0.54], self-reported frequency (AROC 0.52), self-reported percentage (AROC 0.56) and UPC (AROC 0.58), but moderate for electronic monitoring (AROC 0.70). Correlation was moderate among self-reported measures, adherence (0.61–0.66), but low for these self-reported measures compared with UPC (0.32–0.36) and with electronic monitoring (0.22–0.28).

Conclusion: Electronic monitoring was the only adherence measure with meaningful ability to discriminate between SSDD and less than SSDD plasma tenofovir levels. Correlation between subjective and objective measures was poor. Future research should explore novel approaches to adherence measurement as PrEP moves into demonstration projects and programmatic implementation.

aDepartment of Medicine, Mbarara University of Science and Technology

bEpiCentre/Médecins Sans Frontières

cDepartment of Medical Laboratory Sciences, Mbarara University of Science and Technology, Mbarara, Uganda

dDepartment of Infectious Diseases, University of Manitoba, Winnipeg, Canada

eDepartment of Medicine, Division of Clinical Pharmacology, Johns Hopkins University, Baltimore, Maryland

fDepartment of Global Health

gDepartment of Medicine

hDepartment of Epidemiology, University of Washington, Seattle, Washington

iDepartment of Medicine, Harvard Medical School

jDepartment of Global Health and Populations, Harvard T.H. Chan School of Public Health Center for Global Health, Massachusetts General Hospital, Boston, Massachusetts, USA.

*Members of the “The Partners PrEP Ancillary Adherence Study Team” have been mentioned under Acknowledgements section.

Correspondence to Nicholas Musinguzi, MS, Global Health Collaborative, Mbarara University of Science and Technology, Plot 10/24, Lower Circular Road, Mbarara, Uganda. Tel: +256 787993269; e-mail: nmusinguzi@gmail.com

Received 22 August, 2015

Revised 21 December, 2015

Accepted 4 January, 2016

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Introduction

Oral tenofovir-based preexposure prophylaxis (PrEP) can reduce HIV transmission by over 90% [1,2]; however, the efficacy of PrEP is highly dependent on adherence [3]. An accurate understanding of adherence behavior is therefore critical for interpretation of clinical trial data, as well as anticipating the individual and public health benefits of PrEP as it begins to be used in demonstration projects and clinical settings [4].

Measurement of adherence is challenging. Currently available methods include self-reported adherence, clinic-based pill counts, unannounced pill counts (UPC), pharmacy refill frequency, drug concentrations, and electronic monitoring. Each adherence measurement method has its limitations and no gold standard exists [5]. Although UPC, electronic monitoring, and drug levels are objective methods, they are still susceptible to manipulation [6–9]. For example, individuals can remove pills from bottles just prior to clinic visits without taking them to appear more adherent than they really are, or they may take a pill just prior to a clinic visit only because they are aware that their blood will be drawn for a drug level measurement. UPC may be less susceptible to manipulation [10,11], but the logistics of conducting unannounced visits can be challenging and costly. Self-reported adherence measures are an inexpensive alternative that have been shown to correlate with objective measures for antiretroviral therapy (ART) adherence [12]. Self-report, however, can be subject to recall bias and are often overestimated owing to social desirability [12,13]. Importantly, two clinical trials of PrEP [FEM-PrEP and Vaginal and Oral Interventions to Control the Epidemic] found very high self-reported adherence, yet drug detection was very low [14–16]. Similarly, a recent detailed analysis of PrEP adherence in the Iniciativa Profilaxis Pre-Exposición (iPrEx) trial showed large discrepancies between self-report and drug detection [17].

Additional data are needed on optimal adherence measurement strategies for PrEP. Self-report would be ideal for use in clinical settings, given its low-cost and ease of implementation; however, few studies to date have presented detailed comparisons of self-reported measures to objective measures for PrEP adherence [17–19]. Importantly, questions used for self-reported adherence vary and some questions may be more accurate than others in a given population because of individual and/or cultural preferences. Moreover, the cognitive processes involved in recalling adherence behavior beyond a few doses are likely more of an estimation (e.g. rating of ability to take medication as prescribed) than an enumeration (e.g. frequency or percentage of doses taken) [20]. Previous studies have found self-reported rating of adherence to more closely align with objective measures than frequency or percentage [21–23]; however, no such studies had been performed for PrEP in resource-limited settings.

In this analysis, we compared three types of self-reported adherence questions (rating of ability to adhere, frequency of doses taken, and percentage of doses taken) with three forms of objective adherence measurement (UPC, electronic monitoring, and plasma tenofovir levels) using data from an ancillary adherence study within a clinical trial of PrEP among serodiscordant couples in East Africa (the Partners PrEP Study).

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Methods

Partners preexposure prophylaxis study

The Partners PrEP Study was a phase III, randomized, double blind, placebo-controlled, three arm clinical trial conducted on the HIV uninfected partner of 4747 serodiscordant couples at nine research sites in Kenya and Uganda. Enrolment began in July 2008 and concluded in November 2010. The HIV-uninfected partner was randomly assigned to one of three arms: once daily tenofovir (TDF), combination emtricitabine/tenofovir (FTC/TDF), or identical placebo. Study design, procedures and outcomes have been previously described [24]. In July 2011, the independent Data and Safety Monitoring Board recommended discontinuation of the placebo arm after the TDF and FTC/TDF arms had demonstrated 67 and 75% efficacy, respectively.

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Partners preexposure prophylaxis ancillary adherence study

In November 2009, an ancillary study was initiated to objectively measure and support adherence at three of the Uganda Partners PrEP Study sites (Kabwohe, Kampala, and Tororo). A convenience sample of 1147 individuals was selected from participants enrolling in the main study or those already enrolled who had at least 6 months left of follow-up. Study participants were selected from all three study arms. Details of the ancillary adherence study have also been previously described [1].

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Adherence measurements

In the Partners PrEP Study, adherence was measured by pill counts at monthly study visits and blood was stored for later selected determination of plasma tenofovir levels. Tenofovir levels were quantified by the Clinical Pharmacology Analytical Laboratory at the Johns Hopkins University School of Medicine using previously described ultra-performance liquid chromatographic-tandem mass spectrometric methodologies [25]. Calibration standards for assay ranged from 0.31 to 1280 ng/ml [25]. The lower limit of detection was 0.31 ng/ml. In the ancillary adherence study, adherence was additionally measured by the following three methods:

  1. pill counts at unannounced home visits (UPC), which were performed approximately monthly for the first 6 months, then quarterly thereafter (i.e. participants were told such visits would be conducted but the day was not specified);
  2. electronic monitoring using pill bottles (the medication event monitoring system, or MEMS) from which data on bottle openings was downloaded at monthly study visits; and
  3. self-reported questions administered at monthly study visits. Following a short preamble to normalize adherence challenges, the following three types of self-report assessments were administered:self-reported rating: ‘Please tell me your ability to take study pill’ (responses categorized as very poor, poor, fair, good, very good, excellent);self-reported frequency: ‘Did you take your study tablets all the time?’ (responses categorized as none of the time, a little of the time, some of the time, a good bit of the time, most of the time, all of the time); andself-reported percentage: ‘What percentage of the time were you able to take the study tablets exactly as directed?’ (categorized in 10% increments, ranging from 0 to 100%).
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Ethics statement

The human study participants’ committees of Massachusetts General Hospital/Partners Healthcare, the University of Washington, the Centers for Disease Control and Prevention, the Uganda National Council for Science and Technology, and the Uganda Virus Research Institute Science and Ethics approved the study protocol.

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Statistical analysis

We analyzed the first 6 months of PrEP use in the ancillary adherence study for each participant. This time period was chosen because all adherence measurements were collected monthly and could be readily compared. As has been done previously [21], self-reported rating and self-reported frequency response categories were assigned quantitative adherence in 20% increments. For example, the lowest category (e.g. ‘very poor’ for self-reported rating) was assigned 0% and the highest category (e.g. ‘all of the time’ for self-reported frequency) was assigned 100%. UPC adherence was calculated as the number of pills expected for the month minus the pills present at the count divided by the number of days in the month. Electronic monitoring adherence was compiled as the total number of pill bottle openings divided by the number of days of interest (e.g. 28 days in the month). Staff openings of the electronic monitoring bottles and days when a protocol-defined drug hold was in effect (e.g. for adverse events or pregnancy) were excluded. Adherence was capped at 100% (e.g. when the openings exceeded the number of days in the month). Electronic monitoring was also similarly calculated for the 7 days prior to the collection of samples for tenofovir determination to match the window for detection of tenofovir in plasma [26]. Steady-state daily dosing (SSDD) was defined as drug levels not below 40 ng/ml [25]. In a sensitivity analysis, we further explored the threshold consistent with any dosing in the past week (>0.31 ng/ml) [25].

We investigated the predictive validity, correlation, and bias among the adherence measures. Predictive validity was assessed in three ways. First, we constructed a generalized estimating equations (GEE) model for each self-reported measure regressed against SSDD plasma tenofovir. Second, we plotted receiver–operating curves for each measure against SSDD plasma tenofovir and compared the area under the curve. Lastly, we used linear models to assess the proportion of variation in tenofovir levels explained by each of the subjective and objective measures (indicated by R2); measures were assessed individually and then in combination. To test correlation, we computed the Spearman rank correlation coefficient (ρ) on monthly adherence. We computed the bias for each self-reported measure as the difference between the measure and the monthly electronic monitoring adherence, and tested the hypothesis of no bias using GEE with Huber White sandwich standard errors. The level of statistical significance was set at 5%. All statistical analyses were conducted using Stata 13.0 (Stata Corp., College Station, Texas, USA).

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Results

Participant characteristics

A total of 1147 participants contributed 6048 person-months with a median follow-up of 5.5 in the ancillary adherence study [interquartile range (IQR) 5.5, 5.5] months per participant. Participants were followed for a minimum and maximum of 1 and 6 months, respectively, in this analysis. Participant characteristics potentially relevant to adherence behavior have been previously described [1]. Briefly, 53% were male and the median age was 34 years (IQR: 30, 40). More than half (59%) were farmers with moderate education. The prevalence of heavy alcohol use and depression was 9 and 5% respectively. Duration of prior PrEP use at enrollment into the ancillary adherence study varied from 0 to 19+ months. Nearly all (98%) partners were living together, most (80%) had children together, and a quarter were in polygamous marriages. Approximately two-thirds of the couples (66%) had disclosed their HIV serodiscordant status to another person.

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Adherence

The median adherence was 90, 93, and 97% for the self-reported measures (self-reported rating, self-reported frequency, and self-reported percentage, respectively), and 99, and 97% for UPC and electronic monitoring respectively; the data were generally left-skewed (Fig. 1). The median time between electronic monitoring openings was 24 h (IQR: 23.5–24.5); the median number of more than 48 h gaps between electronic monitoring openings over the 6-month analysis period was 2 (IQR: 1–6). Perfect (100%) adherence was most common with self-reported frequency and UPC (66% of participant-months in each method) and least common with self-reported rating (50% of participant-months). Less than optimal adherence (<80%) [1] was most commonly seen with self-reported rating (10% of participant-months) and electronic monitoring (12% of participant-months). Of note, 18% of participant-months for electronic monitoring were capped because of adherence more than 100%. Eighty-nine percent of these exceeded the anticipated adherence by at least two additional doses (i.e. 100–110% adherence). Tenofovir drug levels were assessed on 486 randomly selected blood samples taken from 365 participants (32%) in the ancillary adherence study. Age, gender and study arm distribution in these 365 participants were similar to that of the total cohort in the adherence study [1]. Prevalence of SSDD was 74% (n = 358) of the 486 samples.

Fig. 1

Fig. 1

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Predictive validity

As shown in Fig. 2, mean adherence was nonsignificantly higher in participants with SSDD plasma tenofovir levels compared with those with less than SSDD: 89 versus 85% (P = 0.08) for self-reported rating, 93 versus 91% (P = 0.18) for self-reported frequency, and 96 versus 93% (P = 0.05) for self-reported percentage. In examining the objective measures, mean adherence was significantly higher in participants with SSDD versus those with less than SSDD: 97 versus 92% (P = 0.02) for UPC, 93 versus 72% (P < 0.001) electronic monitoring adherence for the 28 days prior to sample collection for tenofovir determination, and 94 versus 79% (P < 0.001) for 7 days prior to sample collection. Of all adherence measures, electronic monitoring explained the most variability (5.5%) in tenofovir levels. Inclusion of any or all other adherence measures explained an additional less than 1%.

Fig. 2

Fig. 2

As shown in Fig. 3, the area under the receiver–operating curve (AROC) for all self-reported measures and for UPC was low (0.51–0.54). Electronic monitoring adherence showed the highest AROC of 0.70 [95% confidence interval (CI), 0.64, 0.76] for the 7 days and 0.68 (95% CI, 0.61, 0.74) for the 28 days prior to collection of the tenofovir samples. In the sensitivity analysis considering the threshold consistent with any dosing in the past week (>0.31 ng/ml), we found no differences in the magnitude of discrimination for any adherence measure compared with the SSDD threshold. Discrimination of SSDD with UPC, however, lost statistical significance (P = 0.09).

Fig. 3

Fig. 3

Of note, of the 128 participant-months with less than SSDD, 43 participant-months from 40 participants were found to have 100% electronic monitoring adherence for the 7 days prior to sample collection.

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Correlation

As shown in Table 1, pairwise Spearman's correlation (ρ) of monthly self-reported adherence ranged between 0.32 and 0.36 when compared with UPC and between 0.22 and 0.28 when compared with electronic monitoring. Correlation among the self-reported measures ranged between 0.61 and 0.66. All correlations were statistically significant (P < 0.001).

Table 1

Table 1

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Bias

Overall mean electronic monitoring adherence was 3.9% points (95% CI 3.1, 4.8; P < 0.001) higher than self-reported rating. However, it was 0.7% points (CI –1.5, 0.2, P = 0.12) lower than self-reported frequency and 3.3% points (CI –4.1, –2.5, P < 0.001) lower than self-reported percentage. As shown in Fig. 4, pairwise agreement was generally better at higher levels of adherence (≥80%) compared with lower levels of adherence. At these lower levels, mean electronic monitoring adherence was higher than self-reported frequency, as well as for self-reported rating.

Fig. 4

Fig. 4

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Discussion

In a cohort of East African serodiscordant couples participating in a clinical trial of PrEP, adherence was high by multiple forms of self-report, UPC and electronic monitoring; tenofovir drug levels were moderately high. Despite the similarities in overall adherence values (e.g. medians), correlation between subjective and objective measures was poor and only electronic monitoring was able to meaningfully discriminate between steady state and less than SSDD plasma tenofovir levels. Tenofovir drug levels serve as an important benchmark for comparison with other adherence measures, as they document medication ingestion. Like any adherence measure, however, drug levels have limitations, including assay failure, variable drug metabolism within and among individuals, and a relatively short half-life in plasma [26]. Additionally, a dose taken just prior to determination of a drug level will mask nonadherence in the prior several days. Our findings underscore the complexity in accurately measuring adherence behavior.

The three self-reported measures had similar inability to discriminate between SSDD and less than SSDD tenofovir with AROCs equivalent to a coin flip. The recent analysis within the iPrEx trial also found low predictive validity for self-reported adherence with an AROC of approximately 0.5 [17]. Similarly, in the FEM-PrEP trial, the positive predictive value of self-reported adherence compared with tenofovir levels was low, ranging between 28.7 and 42.2% when averaged over time [16].

The poor correlation between subjective and objective measures (ρ: 0.22–0.36) was likely due in part to social desirability and recall bias in self-reported adherence measurements, and is consistent with prior studies of both PrEP and ART adherence [12,17,19,27]. The statistical significance of these correlations is likely driven by the large number of participant-months, rather than clinically meaningful relationships. Of note, the low level of correlation may be partially explained by the clustering of self-reported adherence values in this analysis (i.e. six categories for self-reported rating and self-reported frequency and 11 categories for self-reported percentage) compared with continuous adherence with the objective measures. Importantly, within the TDF2 trial, a correlation analysis yielded a phi coefficient of 0.28 [18] and moderate correlation has been seen with self-report and drug levels for ART [28]. It is therefore possible that self-report may have limited validity in some settings.

Correlations among the three types of self-reported measures (ρ: 0.61–0.67) were higher; however, the distribution of the three self-reported measures differed. Self-reported rating had the widest distribution and identified individuals with low adherence, suggesting that this type of adherence question may be most informative for identifying adherence challenges. Similar findings have been seen in prior analyses of ART adherence measurements [21–23]. Indeed, the goal with self-reported adherence is often described as ‘pulling people off the ceiling’ – even if self-reported adherence is overestimated, those reporting less than perfect adherence may benefit from additional adherence support.

Interestingly, average self-reported rating was lower than electronic monitoring adherence. Self-reported adherence is typically higher than objective measures, suggesting that individuals may have underestimated their adherence when creating this type of adherence estimation. Lower self-reported adherence when the corresponding electronic monitoring adherence was also low or moderate has been observed previously [29,30], suggesting that participants may be overly self-critical whenever their adherence is less than optimal. Cognitive testing has been used to understand the performance of different types of self-report [31] and may be beneficial in this setting to understand how this population views adherence behavior. Alternatively, higher electronic monitoring than self-reported adherence may have been introduced by extra electronic monitoring openings unassociated with dosing.

This analysis also identified noteworthy findings among the objective adherence measures. First, a low ρ correlation was found between UPC and electronic monitoring adherence (0.4). Although predictive validity for UPC was statistically significant, discrimination between SSDD and less than SSDD plasma tenofovir was lower than that of electronic monitoring (AROC 0.58 versus 0.68, respectively). These findings suggest UPC may have been subject to manipulation (e.g. pill dumping despite the unannounced nature of the pill count). One potential limitation of the comparisons of UPC and electronic monitoring with plasma tenofovir is the difference in monitored times in which UPC and electronic monitoring reflect 1 month of adherence behavior, whereas the window for detection of tenofovir in plasma is 7 days. The findings for 28-day and 7-day electronic monitoring adherence, however, are similar. Overall, 43 participant months had 100% 7-day electronic monitoring adherence, but less than SSDD tenofovir suggesting that in some cases, participants may have manipulated the electronic monitoring devices (e.g. opening the device without taking the pill), although assay failure and/or atypical drug metabolism could have impacted the tenofovir findings. Importantly, the number of participants with highly discrepant adherence by electronic monitoring and plasma tenofovir level reflects only 11% of participants randomly selected for tenofovir level determination).

The strength of this analysis lies in the large sample with multiple measures of adherence; however, there are also limitations. First, the time frames associated with the subjective and objective adherence measures were mismatched compared with the tenofovir drug quantification (28 versus 7 days) as noted above, and only electronic monitoring adherence could be adjusted. Additionally, a sample of participants was used for determining plasma tenofovir levels among approximately one-fifth of the cohort. Although the sampling was random, some bias may have been present.

In sum, adherence is paramount for PrEP efficacy in reducing HIV transmission, yet characterizing adherence behavior remains challenging. Although the low cost and ease of implementation associated with self-reported adherence makes it an ideal candidate for adherence measurement in future studies and clinical implementation of PrEP, our findings suggest that self-reported adherence may be inaccurate, even when geared toward estimation rather than enumeration. Moreover, objective adherence measures have limitations in accuracy as well, including possible manipulation and/or technical failures. Future efforts should explore novel approaches to PrEP adherence measurement. For example, cognitive testing may help identify more informative self-report questions [31]. Short messaging service may allow for more frequent assessment of self-report, thus reducing recall bias, as well as potentially reducing social desirability through the relative anonymity of the technology. Real-time adherence monitoring may improve accuracy of electronic monitoring through rapid identification of technical failures, and also has the added potential for delivery of real-time adherence feedback and/or intervention [32,33]. Pharmacokinetic measures (e.g. drug levels in dried blood spots, hair) [19,34,35] that provide an understanding of adherence over longer time periods compared with plasma are desirable [36]. These or other measurement approaches will be critical for defining the adherence–efficacy relationship as PrEP is rolled out beyond clinical trials. Ongoing assessment of adherence behavior in demonstration projects and programmatic implementation will be important, because motivations, facilitators, and barriers to adherence may differ (e.g. known PrEP efficacy, intensity of counseling).

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Acknowledgements

The authors would like to thank the study participants, DF/Net Inc. for data coordination, Stephen Becker from the Bill and Melinda Gates Foundation, and the study teams: Tororo (Aloysious Kakia, Michael Enyakoit and other team members); Kampala (Edith Nakku-Joloba, Kenneth Mugwanya, and other team members); and Kabwohe (Stephen Asiimwe, Alex Kintu, Deo Agaba, Rogers Twesigye, and other team members).

Massachusetts General Hospital and Harvard University (Boston, Massachusetts, USA): David Bangsberg, Jessica Haberer, Stephen Safren, Christina Psaros, Norma Ware, Monique Wyatt University of Washington (Seattle, Washington, USA): Connie Celum, Jared M Baeten, Deborah Donnell Johns Hopkins University (Baltimore, Maryland, USA): Craig Hendrix Kabwohe Clinical Research Center (Kabwohe, Uganda): Elioda Tumwesigye, Stephen Asiimwe Makerere University (Kampala, Uganda): Elly Katabira, Allan Rolland, Edith Nakku-Joloba Centers for Disease Control and Prevention-Uganda and The AIDS Support Organization (Tororo, Uganda): James Campbell, Aloysious Kakia.

The study drug was donated by Gilead Sciences, California, USA.

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Conflicts of interest

There are no conflicts of interest.

Portions of this data were presented at the Conference on Retroviruses and Opportunistic Infections, Seattle, Washington (23–26 February 2015).

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Keywords:

adherence; drug levels; East Africa; objective adherence; preexposure prophylaxis; serodiscordant; subjective adherence; tenofovir

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