Adherence to antiretroviral therapy (ART) is required to achieve and sustain virologic suppression (VS).1 A multitude of adherence measures exist but there is no gold standard, and measuring ART adherence in both routine care and research settings is a major challenge.2 Self-reported adherence frequently overestimates actual treatment adherence,3 whereas HIV viral load, which is often used as a marker of ART adherence, does not capture patterns of adherence or discriminate between poor adherence and resistance as causes of virologic failure.2
Measuring antiretroviral (ARV) drug concentrations has limitations but is an objective way to assess ART adherence.2 Plasma concentrations of the ARVs tenofovir (TFV) and efavirenz (EFV), which are used in first-line ART regimens, are only informative about dosing in the past 4–5 days.4,5 Plasma TFV has a half-life of approximately 14 hours,6 whereas EFV concentrations and half-life vary with CYP2B6 metabolizer genotype.4,7,8 The half-life of EFV 600 mg (the current standard dose) ranges from approximately 16 hours in people considered extensive metabolizers to 49 hours among slow metabolizers,4 complicating the interpretation of plasma EFV concentrations as an adherence measure. An assay has been developed to measure tenofovir-diphosphate (TFV-DP) concentrations in dried blood spots (DBS).9 TFV-DP in DBS has a half-life of 17 days and can be detected for up to 12 weeks after stopping, a major benefit for assessing long-term adherence.10–12 Both plasma and DBS ARV concentrations are measured using complex and expensive laboratory assays, and neither is likely to be feasible outside of the context of clinical trials.
To date, most data on DBS TFV-DP as an adherence measure have been obtained from HIV-negative individuals in pre-exposure prophylaxis (PrEP) studies. There are very few studies reporting TFV-DP DBS concentrations or therapeutic concentration thresholds for detection of viral suppression and thus ART adherence in people living with HIV (PLWH). Two small studies compared DBS TFV-DP with other adherence measures: pharmacy refill adherence among 35 women in the United States10 and electronic drug monitoring in South Africa (n = 29).13 Only one study has reported on the ability of TFV-DP in DBS to predict VS.11 In addition, little is known about how TFV-DP in DBS compares with less expensive plasma ARV drug concentrations or other more affordable adherence measures such as self-reported adherence that could be used in low-resource settings. Existing data on TFV-DP concentrations in DBS indicate that concentrations are up to 19% lower in men than in women12 and that there seem to be differences across populations with lower concentrations among black compared with white or Hispanic individuals.11 African women bear the largest burden of the HIV epidemic, but to date, there is just one unpublished report on TFV-DP in DBS in an African cohort on ART,13 and there are no data on the ability of TFV-DP in DBS to predict VS among African women. Here, we describe plasma EFV, plasma TFV and DBS TFV-DP concentrations, and self-reported adherence in a cohort of women living with HIV who are on ART in Cape Town, South Africa and assess their relationship with HIV viral load.
Design, Participants, and Setting
Women who were enrolled during pregnancy in a large implementation science study (the MCH-ART study) in Gugulethu, Cape Town, were approached between 36 and 60 months postpartum and invited to participate in this cross-sectional substudy. The MCH-ART study methods and results have been described previously.14,15 All women had initiated the first-line regimen of tenofovir disoproxil fumarate (TDF) 300 mg, emtricitabine 200 mg or lamivudine 300 mg (XTC), and EFV 600 mg, provided as a once-daily fixed-dose combination. For this substudy, the first 150 women who agreed to participate were recruited and had blood drawn for ARV assays. Women who were pregnant or had switched to second-line ART were excluded.
During the study visit, all women completed structured face-to-face interviews in the predominant local language, isiXhosa. Self-reported medication adherence in the past 30 days was measured using a simple, 3-item scale that has been described previously and is presented in Table 1, Supplemental Digital Content, http://links.lww.com/QAI/B302.16,17 Women reported on their current ART use and which regimens they were taking. ART regimen history was reviewed using the provincial electronic pharmacy records. Women were asked to report their current pregnancy status, and their height and weight were measured by study staff members who were trained in anthropometric techniques. Weight was measured using a standing scale and height using a stadiometer with equipment calibrated regularly.
ARV Drug Assays and Viral Loads
Venous EDTA blood samples were drawn from each participant and kept below 4°C until they were processed for storage. Within 6 hours of collection, samples were centrifuged at 3500 rpm and plasma decanted into cryovials, before being frozen at −80°C. Most specimens were collected in the mid-dose interval (12–18 hours after dose). For the TFV-DP DBS assay, 50 µL of whole blood was pipetted onto Whatman 903 Proteinsaver cards, allowing it to dry overnight at room temperature and then stored desiccated in airtight freezer-safe bags at −80°C.
EFV, TFV, and TFV-DP were analyzed with validated liquid chromatography–tandem mass spectrometry assays by the Clinical PK Laboratory, Division of Clinical Pharmacology, University of Cape Town. EFV plasma concentrations were determined, as described by Bienczak et al.18 TFV concentrations were determined using a protein precipitation extraction method, with tenofovir-d6 as the internal standard, followed by high-performance liquid chromatography with MS/MS detection using an AB SCIEX API 3000 instrument. Gradient chromatography was performed on a Waters Atlantis T3 (C18, 3 µm, 100 × 2.1 mm) analytical column. The mobile phase consisted of 0.1% formic acid in water and 0.1% formic acid in acetonitrile and was delivered at a flow rate of 300 µL per minute. The analyte and internal standard were monitored at mass transitions of the protonated precursor ions m/z 288.1 and m/z 294.1 to the product ions m/z 176.2 and m/z 182.2 for tenofovir and tenofovir-d6, respectively. The calibration curve fitted a quadratic (weighted by 1/concentration) regression over the ranges 10–1600 ng/mL. TFV-DP in DBS was indirectly measured using a slightly modified LC-MS/MS assay, as described by Castillo-Mancilla et al.9
An additional venous sample was sent to the National Health Laboratory Services (NHLS) for viral load testing (Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 assay; Roche Diagnostics, Branchburg, NJ).
Routine Medical Records
In addition to data collected from participants during the study visit, routine electronic health records were requested from the Western Cape Provincial Health Data Centre. This included data from the NHLS (for serum creatine and CD4 cell-count measures) and pharmacy databases (to validate ARV regimens), all of which are linked by a unique patient identifier and include all public health facilities in the Western Cape Province. Kidney function is an important consideration when measuring drug concentrations, whereas CD4 cell count is known to be independently associated with viral load; thus, serum creatinine concentrations and CD4 cell counts measured within 6 months before or after the study visit were abstracted from the laboratory records.11,19,20 Serum creatine and age were used to calculate creatine clearance using the CKD-EPI formula for black women.21 Less than 25% of women had recent CD4 cell counts available, so these data were not included. Anemia is also associated with HIV disease and can impact drug concentration measures, particularly in DBS;22 however, measures of hemoglobin or hematocrit were not available in this study.
All analyses were performed in Stata (Stata Corporation, College Station, TX). Means with SDs, medians with interquartile ranges (IQRs), or proportions were used to describe the characteristics of the cohort and the adherence measures. Drug concentrations were also log-transformed and back-transformed to report geometric means with 95% confidence intervals (CIs). Concentrations below the lower limit of quantification (LLOQ) for each assay (0.0195 µg/mL for plasma EFV, 10 ng/mL for plasma TFV, and 16.6 fmol/punch for DBS TFV-DP) were assigned a value half that of the LLOQ (0.00975 µg/mL for plasma EFV, 5 ng/mL for plasma TFV, and 8.3 fmol/punch for DBS TFV-DP).10
Logistic regression models were used to evaluate the relationship between continuous adherence measures and VS. Age, body mass index (BMI), and duration on ART were included as a priori covariates; a subanalysis was conducted among women with creatinine clearance available. VS was defined as viral load <50 copies/mL with sensitivity analyses using thresholds of <400 and <1000 copies/mL. Area under the curves (AUCs) of receiver operating characteristics (ROC) was used to assess discrimination of the adherence measures to predict VS. ROC AUCs for each drug concentration and self-reported adherence were compared using χ2 tests for equality of AUCs proposed by De Long et al.23 We estimated sensitivity, specificity, and positive predictive value (PPV) and negative predictive value (NPV) using established drug concentration thresholds: ≥0.7 µg/mL for plasma EFV,24,25 ≥35.5 ng/mL for plasma TFV,26 and 5 adherence thresholds (<350, 350–699, 700–1249, 1250–1849, and ≥1850 fmol/punch) for TFV-DP from DBS which were determined in a healthy volunteer study.11,12 We also examined which thresholds of each of the continuous drug concentrations would maximize both sensitivity and specificity to detect women with and without VS. Sensitivity analyses were conducted excluding women who reported taking no ART in the past 30 days, a group in whom drug concentrations may not be measured in a routine care setting. Women who were pregnant at the time of the study visit27 or who had switched to second-line ART regimens were excluded from all analyses.
Finally, we examined whether there was improved short-term ART adherence related to the study visit among participants (so called “white coat” adherence2,28), by comparing plasma TFV concentrations, with a relatively short half-life of approximately 14 hours6 indicating recent dosing, with TFV-DP concentrations in DBS, with a half-life of up to 17 days12 indicating consistent dosing over the recent weeks.
All participants completed written informed consent, including consent for specimen storage and drug assays, before completing any study procedures. This study was reviewed and approved by the University of Cape Town Human Research Ethics Committee and the Columbia University Institutional Review Board.
Thirteen of the 150 consecutive women screened were excluded (7 were pregnant and 6 had switched to second-line ART regimens). The characteristics of 137 women enrolled into the study are displayed in Table 1. At the study visit, the median time on ART was 3.9 years (IQR: 3.7–4.0) and 88 women (64%) were virologically suppressed (<50 copies/mL).
The distribution of plasma EFV, TFV, and DBS TFV-DP concentrations is presented in Table 2 and Figure 1, Supplemental Digital Content, http://links.lww.com/QAI/B302. Specimens were collected at a median of 15 hours after the last dosing (IQR: 14–16). In total, 84%, 76%, and 86% of women had any detectable plasma EFV, plasma TFV, and DBS TFV-DP, respectively. There were 38 women (28%) who had drug concentrations below the LLOQ for all 3 ARV assays; 2 of these 38 women were virologically suppressed. These 2 women reported that they were no longer taking ART, and this was confirmed in medical records. Both women were virologically suppressed from the time of ART initiation, and their HIV diagnosis was confirmed on ELISA. Overall, most women had high self-reported adherence scores with 56% of women (n = 77) reporting 100% adherence in the last 30 days on the 3-item scale; 62 of whom (81%) were virologically suppressed.
In ROC analyses, to evaluate how well each adherence marker predicted VS, DBS TFV-DP had the highest AUC of 0.926 (95% CI: 0.876 to 0.976) after adjusting for age and duration on ART (Fig. 1; unadjusted ROC curves are shown in Figure 2, Supplemental Digital Content, http://links.lww.com/QAI/B302). This was significantly better than plasma TFV (AUC = 0.864 95% CI: 0.797 to 0.932, P = 0.006) but not significantly different from plasma EFV (AUC = 0.903 95% CI: 0.839 to 0.967, P = 0.138). All drug concentrations performed better than 30-day self-reported adherence (AUC = 0.756 95% CI: 0.660 to 0.852, P <0.05 for each assay).
Using drug concentrations to predict VS, we used ROC analyses to examine the diagnostic characteristics of different drug concentration cutoff points, including established thresholds for TFV-DP in DBS,11 plasma TFV,26 and plasma EFV24,25 (Table 3). Having any detectable drug concentration on any of the 3 assays was highly predictive of VS. Almost 90% of the cohort was correctly classified as virologically suppressed or not suppressed based on any detectable TFV-DP in DBS or any plasma EFV; 85% were correctly classified as virologically suppressed or not by any detectable plasma TFV. Higher drug concentration cutoffs resulted in higher positive predictive values.
Thresholds of DBS TFV-DP have been shown to relate back to doses taken per week in healthy volunteers.11Table 4 examines in more detail the viral load distribution and association between VS and DBS TFV-DP in our cohort within these established thresholds. In our cohort, 97% of women (n = 29) who had a DBS TFV-DP concentration ≥1250 fmol/punch were virologically suppressed (defined as <50 copies/mL). This threshold also perfectly predicted viral loads <400 and <1000 copies/mL. Seven of the 47 women (15%) in the lowest TFV-DP category, <350 fmol/punch, remained suppressed despite none or very low drug concentrations. A dose-response relationship was observed between VS and increasing concentrations of TFV-DP in DBS; this was not observed for increasing concentrations of plasma EFV or TFV (data not shown). Similar associations were observed in sensitivity analyses, excluding women who self-reported not taking any ART in the past 30 days (see Table 2, Supplemental Digital Content, http://links.lww.com/QAI/B302). Increasing years of age (aOR: 1.12 95% CI: 1.0 to 1.25) was associated with VS, whereas the association between suppression and increasing duration on ART had very wide CIs (aOR: 1.56 95% CI: 0.13 to 18.07) and was not statistically significant (crude models in Table 3, see Supplemental Digital Content, http://links.lww.com/QAI/B302). Creatinine clearance was not measured at the time of the drug concentration testing, and only 74 women had available serum creatinine concentrations in the 6 months before or after the study visit. In this group, creatinine clearance was not associated with VS. Neither creatinine clearance nor BMI changed the associations between drug concentrations and viral load and was therefore not included in adjusted models.
To examine improved short-term ART adherence related to the study visit among participants, or “white coat” adherence,2,28 we compared plasma TFV concentrations (indicating recent dosing) with concentrations of TFV-DP in DBS (indicating consistent dosing in recent weeks). Concentrations of TFV-DP in DBS correlated well with plasma TFV concentrations (r = 0.700, see Figure 3, Supplemental Digital Content, http://links.lww.com/QAI/B302). There were 4 women with any detectable plasma TFV but DBS TFV-DP concentrations below 350 fmol/punch. All 4 women also had detectable plasma EFV concentrations, and only 2 women had viral loads above 50 copies/mL (see Table 4, Supplemental Digital Content, http://links.lww.com/QAI/B302).
Our findings from a cohort of South African women show that concentrations of TFV-DP in DBS, plasma EFV, and plasma TFV were all strongly associated with VS, and all performed better than self-reported adherence. The strength of association between DBS TFV-DP and VS increased with increasing drug concentrations and remained consistent after adjustment for covariates and in sensitivity analyses, confirming recent findings in a US cohort.11 This study is the first to compare TFV-DP in DBS with plasma ARV concentrations and HIV viral load for measuring ART adherence in an African population and adds novel insights for the potential use of TFV-DP in DBS and plasma EFV or TFV to measure adherence among PLWH.
Both plasma EFV and DBS TFV-DP concentrations above the LLOQ had sensitivities approaching 100% and correctly identified 89% of women with VS. We found a stronger association between plasma EFV concentrations and VS than previously reported in a similar population up to 1 year on ART.7 Adherence is known to change over time, and there may be less intermittent adherence in our cohort at 3–4 years after ART started compared with the first year on ART. However, there are mixed results in the literature regarding the association between increasing duration on ART and adherence.29 Although we were not able to measure the genes relevant to EFV metabolism in this study, it is likely that women with EFV concentrations above 4 µg/mL (11% of our cohort) possess the CYP2B6 slow metabolizer genotype resulting in a longer EFV half-life.8 The longer DBS TFV-DP half-life and possibly longer EFV half-life compared with that of plasma TFV may explain why, even when administered in a fixed-dose combination, plasma TFV concentrations performed slightly worse than plasma EFV and TFV-DP in DBS at predicting VS. There were 2 women in the cohort with no detectable drug concentrations and suppressed viral loads, and both were believed to be elite controllers.
TFV-DP concentrations in DBS among virologically suppressed women in our cohort (geometric mean 815 fmol/punch, median 961 fmol/punch) were similar to values reported in another South African cohort of predominantly women (median 939 fmol/punch).13 However, they were lower than those observed among suppressed black PLWH in the United States (geometric mean 1453 fmol/punch)11 and higher than that observed among nonpregnant HIV-negative African women on PrEP in Uganda and Kenya (mean 637 fmol/punch).27 This supports recent findings that virologically suppressed PLWH have higher DBS TFV-DP concentrations than HIV-negative individuals on PrEP.11 This comparison of our findings with existing studies also suggests that therapeutic thresholds of DBS TFV-DP may be lower among black African PLWH compared with PLWH of other ethnicities, and further research is needed to establish therapeutic adherence thresholds for DBS TFV-DP concentrations in this population. Although we observed lower TFV-DP concentrations in DBS than those in the study by Castillo-Mancilla et al,11 we found a similar dose-response relationship between VS and increasing TFV-DP concentrations in DBS. In contrast to previous findings,11 we found no association between TFV-DP in DBS and BMI, which may be due to most women in our cohort having BMI ≥25 kg/m2. Other characteristics such as chronic kidney disease, anemia, or use of concomitant medication (eg, ritonavir or cobicistat) may also influence TFV-DP concentrations in DBS among PLWH,11,19,20,22,30 but we were not able to evaluate these in our study. We were also unable to assess variability in TFV-DP concentrations in DBS because of ARV regimen, race, or gender because our cohort was restricted to nonpregnant women on a first-line FDC regimen of TDF + XTC + EFV. Pregnancy status has also recently been shown to influence TFV-DP concentrations in DBS among African women on PrEP,27 and this requires further evaluation in the context of HIV infection.
Our findings should be interpreted with the following additional limitations in mind. Previous studies have accounted for CD4 cell count, kidney function, and anemia in their analyses;10,11 however, these data were not collected by the study, and although effort was made to abstract information from routine medical records, few women had available measures within 6 months before or after the study visit. We ascertained ART regimen by self-report and through triangulation with routine pharmacy dispensing data, but errors may have occurred. In this cross-sectional study, we were also unable to assess daily dosing or to match drug concentration thresholds to actual ART dosing before the study visit because the last dose was not observed. Given the observed differences in TFV-DP concentrations in DBS among people living with and without HIV, as well as the lower concentrations reported among black individuals, further research is needed to evaluate adherence thresholds in African populations living with HIV.
In both research and routine care, there is often concern about improved adherence shortly before a scheduled research or clinical visit, or “white coat” adherence.2,28 We found little evidence of this in our cohort with only 4 women with therapeutic plasma TFV but TFV-DP in DBS below 350 fmol/punch. The long half-life of TFV-DP in DBS and the dose-response relationship with VS show that measuring TFV-DP in DBS provides a more nuanced measure of adherence than plasma EFV or TFV concentrations. However, our findings suggest that plasma EFV and TFV can also be strong predictors of VS and support the use of both plasma and DBS drug concentrations for measuring ARV adherence among PLWH in research settings. Both plasma and DBS assays were superior to self-reported adherence in this analysis, but both are costly and require laboratory testing, with the associated logistical challenges of transport, storage, and laboratory capacity. These practical considerations prohibit their use in resource-limited settings, and the development of noninvasive, point-of-care drug concentration measures for the measurement of adherence to PrEP and HIV treatment, such as urine testing,31,32 should remain a research priority.
In summary, our data add to the evidence on the use of TFV-DP in DBS for monitoring ART adherence in PLWH, providing new insights from a cohort of African women. TFV-DP in DBS and plasma EFV and TFV concentrations were strongly associated with VS and are superior to self-reported adherence. Further research is needed into less expensive and point-of-care technologies as well as to assess the added value of drug concentration assays in the context of viral load monitoring and screening for ART resistance.
The authors thank the women who participated in this study and the study staff in Gugulethu for their support of this research.
1. World Health Organization. Consolidated Guidelines on the Use of Antiretroviral Drugs for Treating and Preventing HIV Infection: Recommendations for a Public Health Approach. Geneva, Switzerland: WHO; 2016.
2. Castillo-mancilla JR, Haberer JE. Adherence measurements in HIV : new advancements in pharmacologic methods and real-time monitoring. Curr HIV/AIDS Rep. 2018;15:49–59.
3. Stirratt MJ, Dunbar-Jacob J, Crane HM, et al. Self-report measures of medication adherence behavior: recommendations on optimal use. Transl Behav Med. 2015;5:470–482.
4. Dickinson L, Amin J, Else L, et al. Pharmacokinetic and pharmacodynamic comparison of once-daily efavirenz (400 mg vs. 600 mg) in treatment-naïve HIV-infected patients: results of the ENCORE1 study. Clin Pharmacol Ther. 2015;98:406–416.
5. Jackson A, Moyle G, Watson V, et al. Tenofovir, emtricitabine intracellular and plasma, and efavirenz plasma concentration decay following drug intake cessation: implications for HIV treatment and prevention. J Acquir Immune Defic Syndr. 2013;62:275–281.
6. Anderson PL, Kiser JJ, Gardner EM, et al. Pharmacological considerations for tenofovir and emtricitabine to prevent HIV infection. J Antimicrob Chemother. 2011;66:240–250.
7. Orrell C, Cohen K, Leisegang R, et al. Comparison of six methods to estimate adherence in an ART-naïve cohort in a resource-poor setting: which best predicts virological and resistance outcomes? AIDS Res Ther. 2017;14:1–11.
8. Sinxadi PZ, Leger PD, McIlleron HM, et al. Pharmacogenetics of plasma efavirenz exposure in HIV-infected adults and children in South Africa. Br J Clin Pharmacol. 2015;80:146–156.
9. Castillo-Mancilla JR, Zheng JH, Rower JE, et al. Tenofovir, emtricitabine, and tenofovir diphosphate in dried blood spots for determining recent and cumulative drug exposure. AIDS Res Hum Retroviruses. 2013;29:384–390.
10. Castillo-mancilla JR, Searls K, Caraway P, et al. Short Communication : tenofovir diphosphate in dried blood spots as an objective measure of adherence in HIV-infected women. AIDS Res Hum Retroviruses. 2015;31:428–432.
11. Castillo-Mancilla JR, Morrow M, Coyle RP, et al. Tenofovir diphosphate in dried blood spots is strongly associated with viral suppression in individuals with human immunodeficiency virus infections. Clin Infect Dis. 2018:ciy708.
12. Anderson PL, Liu AY, Castillo-Mancilla JR, et al. Intracellular tenofovir-diphosphate and emtricitabine-triphosphate in dried blood spots following directly observed therapy. Antimicrob Agents Chemother. 2017;62:e01710–e01717.
13. Warne P, Robbins RN, Anderson PL, et al. Utility of dried blood spot-derived ARV biomarkers as an objective measure of treatment adherence in South Africa. In: 10th International Conference on HIV Treatment and Prevention Adherence, Miami, FL, 2015.
14. Myer L, Phillips TK, Zerbe A, et al. Optimizing antiretroviral therapy (ART) for maternal and child health (MCH): rationale and design of the MCH-ART study. J Acquir Immune Defic Syndr. 2016;72:189–196.
15. Myer L, Phillips TK, Zerbe A, et al. Integration of postpartum healthcare services for HIV-infected women and their infants in South Africa: a randomised controlled trial. PLoS Med. 2018;15:e1002547.
16. Wilson IB, Lee Y, Michaud J, et al. Validation of a new three-item self-report measure for medication adherence. AIDS Behav. 2016;20:2700–2708.
17. Phillips T, Brittain K, Mellins CA, et al. A self-reported adherence measure to screen for elevated HIV viral load in pregnant and postpartum women on antiretroviral therapy. AIDS Behav. 2017;21:450–461.
18. Bienczak A, Cook A, Wiesner L, et al. The impact of genetic polymorphisms on the pharmacokinetics of efavirenz in African children. Br J Clin Pharmacol. 2016;82:185–198.
19. Baxi SM, Greenblatt RM, Bacchetti P, et al. Common clinical conditions-age, low BMI, ritonavir use, mild renal impairment-affect tenofovir pharmacokinetics in a large cohort of HIV-infected women. AIDS. 2014;28:59–66.
20. Lu Y, Goti V, Chaturvedula A, et al. Population pharmacokinetics of tenofovir in HIV-1-Uninfected members of serodiscordant couples and effect of dose reporting methods. Antimicrob Agents Chemother. 2016;60:5379–5386.
21. Michels WM, Grootendorst DC, Verduijn M, et al. Performance of the Cockcroft-Gault, MDRD, and new CKD-EPI formulas in relation to GFR, age, and body size. Clin J Am Soc Nephrol. 2010;5:1003–1009.
22. Wilhelm AJ, den Burger JC, Swart EL. Therapeutic drug monitoring by dried blood spot: progress to date and future directions. Clin Pharmacokinet. 2014;53:961–973.
23. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–845.
24. Orrell C, Bienczak A, Cohen K, et al. Effect of mid-dose efavirenz concentrations and CYP2B6 genotype on viral suppression in patients on first-line antiretroviral therapy. Int J Antimicrob Agents. 2016;47:466–472.
25. Dickinson L, Amin J, Else L, et al. Comprehensive pharmacokinetic, pharmacodynamic and pharmacogenetic evaluation of once-daily efavirenz 400 and 600 mg in treatment-naïve HIV-infected patients at 96 Weeks: results of the ENCORE1 study. Clin Pharmacokinet. 2016;55:861–873.
26. Hendrix CW, Andrade A, Bumpus NN, et al. Dose frequency ranging pharmacokinetic study of tenofovir-emtricitabine after directly observed dosing in healthy volunteers to establish adherence benchmarks (HPTN 066). AIDS Res Hum Retroviruses. 2016;32:32–43.
27. Pyra M, Anderson PL, Hendrix CW, et al. Tenofovir and tenofovir-diphosphate concentrations during pregnancy among HIV-uninfected women using oral preexposure prophylaxis. AIDS. 2018;32:1891–1898.
28. Podsadecki TJ, Vrijens BC, Tousset EP, et al. “White coat compliance” limits the reliability of therapeutic drug monitoring in HIV-1—infected patients. HIV Clin Trials. 2008;9:238–246.
29. Wilson IB, Bangsberg DR, Shen J, et al. Heterogeneity among studies in rates of decline of antiretroviral therapy adherence over time. JAIDS J Acquir Immune Defic Syndr. 2013;64:448–454.
30. Cattaneo D, Minisci D, Baldelli S, et al. Effect of cobicistat on tenofovir disoproxil fumarate (TDF). J Acquir Immune Defic Syndr. 2017;77:1.
31. Haaland RE, Martin A, Holder A, et al. Urine tenofovir and emtricitabine concentrations provide biomarker for exposure to HIV preexposure prophylaxis. AIDS. 2017;31:1647–1650.
32. Koenig HC, Mounzer K, Daughtridge GW, et al. Urine assay for tenofovir to monitor adherence in real time to tenofovir disoproxil fumarate/emtricitabine as pre-exposure prophylaxis. HIV Med. 2017;18:412–418.