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Common clinical conditions – age, low BMI, ritonavir use, mild renal impairment – affect tenofovir pharmacokinetics in a large cohort of HIV-infected women

Baxi, Sanjiv M.a; Greenblatt, Ruth M.a,b,c; Bacchetti, Peterc; Scherzer, Rebeccaa; Minkoff, Howardd; Huang, Yonge; Anastos, Kathrynf; Cohen, Mardgeg; Gange, Stephen J.h; Young, Maryi; Shlipak, Michael G.a,j; Gandhi, Monicaa

doi: 10.1097/QAD.0000000000000033
Clinical Science

Objective: Tenofovir is used commonly in HIV treatment and prevention settings, but factors that correlate with tenofovir exposure in real-world settings are unknown.

Design: Intensive pharmacokinetic studies of tenofovir in a large, diverse cohort of HIV-infected women over 24 h at steady state were performed and factors that influenced exposure [assessed by areas under the concentration–time curves (AUCs)] identified.

Methods: HIV-infected women (n = 101) on tenofovir-based therapy underwent intensive 24-h pharmacokinetic sampling. Data on race/ethnicity, age, exogenous steroid use, menstrual cycle phase, concomitant medications, recreational drugs and/or tobacco, hepatic and renal function, weight, and BMI were collected. Multivariable models using forward stepwise selection identified factors associated with effects on AUC. Glomerular filtration rates (GFRs) prior to starting tenofovir were estimated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation using both creatinine and cystatin-C measures.

Results: The median (range) of tenofovir AUCs was 3350 (1031–13 911) ng × h/ml. Higher AUCs were associated with concomitant ritonavir use (1.33-fold increase, P = 0.002), increasing age (1.21-fold increase per decade, P = 0.0007), and decreasing BMI (1.04-fold increase per 10% decrease in BMI). When GFR was calculated using cystatin-C measures, mild renal insufficiency prior to tenofovir initiation was associated with higher subsequent exposure (1.35-fold increase when pre-tenofovir GFR <70 ml/min, P = 0.0075).

Conclusion: Concomitant ritonavir use, increasing age, decreasing BMI, and lower GFR prior to tenofovir initiation as estimated by cystatin C were all associated with elevated tenofovir exposure in a diverse cohort of HIV-infected women. Clinicians treating HIV-infected women should be aware of common clinical conditions that affect tenofovir exposure when prescribing this medication.

aDepartment of Medicine

bDepartment of Clinical Pharmacy

cDepartment of Epidemiology and Biostatistics, University of California San Francisco (UCSF), San Francisco, California

dDepartment of Medicine, SUNY Downstate Medical Center, Brooklyn, New York

eDepartment of Bioengineering and Therapeutic Sciences, University of California San Francisco (UCSF), San Francisco, California

fDepartment of Medicine, Albert Einstein University, Bronx, New York

gDepartment of Medicine, Stroger Hospital and Rush University, Chicago, Illinois

hDepartment of Medicine, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland

iDepartment of Medicine, Georgetown University Medical Center, Washington DC

jSection of General Internal Medicine, San Francisco Veterans Affairs Medical Center, San Francisco, California, USA.

Correspondence to Monica Gandhi, MD, MPH, Professor of Medicine, Division of HIV/AIDS, UCSF, 405 Irving Street, 2nd floor, San Francisco, CA 94122, USA. Tel: +1 415 502 6285; fax: +1 415 476 8528; e-mail:

Received 24 June, 2013

Revised 13 August, 2013

Accepted 14 August, 2013

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Since approval by the Federal Drug Administration in 2001, tenofovir disoproxil fumarate (TDF) has become one of the most frequently prescribed antiretrovirals in the management of HIV infection [1]. Moreover, TDF is co-formulated into several fixed-dose combinations, which can help promote adherence to combination antiretroviral therapy (cART) [2], and the co-formulation of TDF and emtricitabine is the only agent approved for preexposure prophylaxis in the United States [3,4]. Although mostly effective and safe, TDF has been associated with several major adverse effects in terms of renal function [5] and bone mineral density loss [6,7], both of which can trigger discontinuation of the drug. Adverse effects of medications are generally correlated with systemic levels of the drug and, as is common with many antiretrovirals, TDF demonstrates significant interindividual variability in plasma drug levels [8,9]. The factors that contribute to interpatient variability in TDF pharmacokinetics in diverse and real-world populations, however, are largely unknown.

As with most medications, the dose of TDF that was ultimately marketed for adults (300 mg once daily) with normal renal function was determined during phase I and II studies of the drug [10]. Dose-finding studies usually entail intensive pharmacokinetic evaluations after short-term use in a limited number of volunteers (either HIV-infected or noninfected) who are often homogeneous in regard to race/ethnicity, gender, and/or comorbidities. The generalizability of these pharmacokinetic studies to patients with different characteristics is thereby limited by their inclusion criteria and small sample sizes [11–13]. Broad recognition of important factors that modify a drug's pharmacokinetic parameters once it is used in more diverse populations can be delayed due to limitations in postmarketing tracking procedures or publication bias [14]. To address some of these limitations, we conducted intensive pharmacokinetic studies of TDF in a sample of HIV-infected women in the setting of routine clinical use in order to identify factors associated with drug exposure.

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Study population

The Women's Interagency HIV Study (WIHS) is a large, multicenter, prospective cohort study of HIV-infected women and at-risk HIV-uninfected women in the USA [15]. The WIHS is highly representative of US women living with HIV in terms of age, race/ethnicity, socioeconomic status, concomitant medications, comorbid medical conditions, and so on. We have previously described the ‘WIHS Intensive PK Study’ [16,17], which enrolled a total of 480 HIV-infected women on different cART regimens for 12–24-h sampling of antiretroviral plasma levels after administration of a dose witnessed by study team members under conditions of routine participant use. For this analysis, our study sample consisted of WIHS participants (n = 101) who used TDF for at least 6 months prior to pharmacokinetic evaluation and underwent 24-h intensive pharmacokinetic sampling. Institutional review boards at all participating institutions approved the consent and protocol materials for this study.

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Intensive pharmacokinetic protocol methods

Pharmacokinetic protocols were conducted in clinical research centers or other facilities associated with collaborating WIHS sites. Plasma samples were drawn over 24 h for drug levels under conditions of actual use (including simulation of the participants’ customary diet and administration of other medications). Participants were seen for the pharmacokinetic visit within 6 weeks of their core WIHS visit and data were collected at both visits on weight, comorbidities, HIV RNA level, CD4+ cell counts, self-reported adherence, hepatic and renal function, and illicit substance use. All participants received standard dosing of TDF (300 mg orally once daily) and drug levels were measured in specimens collected at 0, 4, 8, 15, 18, and 24 h after a witnessed dose.

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Laboratory procedures

Plasma levels of TDF were determined by liquid chromatography/tandem mass spectrometry (LC-MS/MS) with TDF-d6 as the internal standard [18]. The plasma sample was pretreated with trifluoroacetic acid for protein precipitation before injecting into the Micromass Quattro Ultima LC-MS/MS system. The assay was validated from 10 to 1000 ng/ml of TDF with a coefficient of variation less than 15% for quality control samples at low, medium, and high concentrations.

Cystatin C was measured in 67 of the 101 women who contributed data to these analyses. Cystatin C in plasma samples was quantified as described previously [19] at the University of California, Los Angeles (UCLA) Clinical Immunology Research Laboratory by a particle-enhanced immunoturbidimetric assay (Gentian, Moss, Norway), which has been calibrated against the new World Standard Reference material ERM-DA471/IFCC [20]. Intraassay coefficients of variation, based on 10 replicates, were less than 2% at serum concentrations of 0.7 and 1.1 mg/l. Interassay coefficients of variation were 4.4 and 3.9% at serum concentrations of 0.8 and 2.2 mg/l, respectively.

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Predictor variables

We analyzed the following variables in relationship to exposure: race (self-reported), age, concomitant medications [including ritonavir (RTV)], HIV RNA and current and nadir CD4+ cell counts, concurrent symptoms or infections, concomitant diabetes or hypertension, use of crack or powder cocaine, alcohol or tobacco, BMI, estimated lean body mass, percentage fat consumption in the diet via self-report, and renal function parameters. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation using serum creatinine from the recent WIHS visit was employed to estimate glomerular filtration rate measures (creatinine-based estimated glomerular filtration rate, eGFRcr) [21] in one set of models. GFR was dichotomized as being more or less than 70 ml/min per 1.73 m2 in our models as this GFR cut-off has clinical significance and the number of women with GFRs less than 60 ml/min per 1.73 m2 were few (n = 3). The models were then repeated using the CKD-EPI equation for cystatin C (cystatin C-based estimated glomerular filtration rate, eGFRcys) [20–22]. Renal function prior to the initiation of TDF for each participant was also assessed using creatinine measures from prior visits (going back up to four visits before starting TDF, if there were missing data). To obtain pre-TDF cystatin C for as many women as possible, we used values more than four visits back when necessary (n = 16 of 67) from archived plasma specimens. All demographic data were collected at the core WIHS visit.

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Outcome variable

Areas under the concentration–time curves (AUCs) were used to estimate TDF exposure over the dosing interval; these were calculated for each individual using the trapezoidal rule [23]. Ten TDF concentrations at the beginning of the dosing interval (C min) in 10 individual participants and one at the third sampling point were below the lower limit of quantification (10 ng/ml); all 11 observations were replaced by 0 ng/ml.

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Statistical analysis

All analyses were conducted using Stata (version 11.2; College Station, Texas, USA) and SAS (version 9.2; SAS Institute, Cary, North Carolina, USA). For multivariate modeling, AUC was logarithmically transformed, and predictors’ coefficients were back-transformed to produce estimated multiplicative effects on geometric mean AUCs. The multivariable model was constructed by forward stepwise selection, with P <0.05 required for entry and retention, but with race (African–American versus others) included because of high a priori interest. As 33% of the participants did not have available cystatin C measures from visits that preceded the start of TDF, we used multiple imputation [24] to reduce the likelihood of possible bias from excluding so many observations from analysis. Multiple imputation with the Markov chain Monte Carlo method was used to impute missing eGFR estimates using cystatin C, with 10 imputations performed to yield approximately 95% relative efficiency [25].

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Characteristics of patient population

TDF levels were measured over a 24-h period for 101 WIHS participants. Table 1 shows the patient characteristics of the study sample (n = 101) and the distribution of relevant covariates, included those that remained in the final multivariate models. The mean age (range) of the participants was 43.1 (21.7–64.9) years. Sixty four women (63%) reported their race as African–American, 24 (24%) Hispanic, and 10 (10%) whites.

Table 1

Table 1

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Summary of pharmacokinetic parameters for tenofovir

The TDF pharmacokinetic parameters for the study population demonstrated significant interindividual variation. The median (range) for the pharmacokinetic parameters were as follows: TDF AUC 3350 (1031–13 911) ng × h/ml; minimum plasma drug concentration (C min) 69.7 (0–363) ng/ml; maximum plasma drug concentration (C max) 251 (81.1–1020) ng/ml; time after administration at which C max was reached (t max) 4.1 (0–24) h; TDF clearance from plasma (CL/F) 322 (77–1047) ml/h. These data are summarized in Table 2 and Fig. 1 shows the concentration–time curves for the 101 participants who underwent intensive pharmacokinetic sampling for TDF levels. All pharmacokinetic curves and t max values are included to reflect conditions of actual use in this cohort.

Table 2

Table 2

Fig. 1

Fig. 1

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Factors associated with tenofovir areas under the concentration–time curve using creatinine-based estimated glomerular filtration rate

In the final multivariate model using the creatinine-based estimate of GFR, race did not substantially influence TDF exposure (Table 3), although older age was associated with higher exposure (increase in AUC by 1.21-fold for every decade of age, P = 0.0007). Concomitant RTV use (present in 61% of all participants) was associated with increased TDF AUC by an average of 1.33-fold (P = 0.0020). Each 10% increase in BMI (kg/m2) was associated with a 0.96-fold reduction in TDF AUC (P = 0.019). An eGFRcr of less than 70 ml/min per 1.73 m2 prior to initiation of TDF was associated with a 1.31-fold higher AUC (P value showed a trend toward statistical significance at 0.094).

Table 3

Table 3

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Factors associated with tenofovir areas under the concentration–time curve using cystatin C-based estimated glomerular filtration rate

In an alternative multivariate analysis (Table 4), GFR was estimated using cystatin C measures and eGFRcys was dichotomized as being at least or less than 70 ml/min per 1.73 m2. As with the models using eGFRcr, race did not substantially affect exposure in this model (P = 0.97). The effect of age on TDF exposure (1.20-fold increase in TDF AUC per decade of age, P = 0.0003) was still prominent. Concomitant RTV use similarly increased exposure by an average of 1.33-fold (P = 0.0014), and higher BMI was similarly associated with a lower (0.96-fold per 10% increase in BMI) TDF AUC (P = 0.025). Mild renal insufficiency (eGFRcys of <70 ml/min per 1.73 m2) preceding the initiation of the TDF-based cART regimen was significantly associated with a 1.35-fold higher AUC for TDF (P = 0.0075).

Table 4

Table 4

Addition of any one of the remaining unselected candidate predictor variables listed in the Methods section under ‘Predictor variables’ resulted in less than 6% change in the estimated effects shown in Tables 3 and 4.

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Although tenofovir is one of the most commonly used antiretroviral agents in both HIV treatment and preexposure prophylaxis settings, limited information is available on the factors that influence its pharmacokinetics under conditions of actual use and in diverse populations. Our study examined factors associated with TDF exposure at steady state in a relatively large sample of HIV-infected women who were taking the drug as part of their prescribed cART regimens. The study participants were highly varied in terms of age, race, comorbid conditions, concomitant medications, and body habitus, similar to patients in clinical practice. We found significant interindividual variation in plasma drug levels, and pharmacokinetic parameters (Fig. 1) in this sample reflecting medication consumption in real-world conditions of actual use. Four common factors were independently associated with greater TDF exposure: older age, preexisting mild renal insufficiency, lower BMI, and concomitant RTV use.

RTV use increased TDF levels, a finding that is consistent with previous studies that have noted a 32–50% increase in TDF AUC when TDF is coadministered with RTV-boosted lopinavir [26,27]. This association is particularly relevant as the concomitant use of TDF and RTV-boosted protease inhibitors is common [28]. A recent analysis in the Adults Clinical Trials Group (ACTG) A5208 study demonstrated that young African women randomized to tenofovir/emtricitabine/lopinavir/RTV had a higher incidence of renal insufficiency compared with women randomized to tenofovir/emtricitabine/nevirapine regimens [29], possibly reflecting higher exposure to tenofovir in the former group. The most likely mechanism underlying this interaction is due to RTV-associated inhibition of specific efflux transporters, specifically the p-glycoprotein (P-gp) or multidrug-resistant-1 (MDR1) transporter, leading to an increase in the intestinal absorption of TDF and its subsequent plasma concentrations [26,30–32].

Our study also demonstrates that lower BMI is associated with modest increases in TDF AUC. Prior studies have demonstrated that low body weight is associated with decreased clearance of TDF [33] and that higher body weight is associated with increased clearance of TDF [34]. Lower eGFR as estimated by cystatin C measured prior to starting TDF (<70 ml/min per 1.73 m2) was associated with a 35% increase in TDF AUC. Although eGFR less than 70 ml/min per 1.73 m2 as estimated by creatinine measures was associated with higher TDF exposure, the link between preexisting kidney function and TDF-AUC was strengthened by estimating GFR using cystatin C measures. Because cystatin C levels are independent of muscle mass, cystatin C is a particularly useful measure in chronically ill, aging populations, or in patients with HIV infection, because artifacts in creatinine-based GFR estimates can occur in individuals with debility or loss of muscle mass [35,36].

There was an independent and unique association of age (up to the maximum age of 65 in this group) with TDF exposure in our models beyond the effect of renal function. The independent association between age and TDF AUC was maintained whether GFR was assessed using creatinine measures or cystatin-C measures, and whether GFR was modeled as a categorical or continuous variable (data not shown). Although recent data have suggested that age is associated with increased protease inhibitor plasma concentrations [37] and age has well known influence on drug pharmacokinetics [38,39], this analysis is the first to report an effect of age on TDF exposure, independent of renal function.

Adverse effects of TDF on renal function have been described [40–42] and dose reductions are currently recommended for patients with marked renal insufficiency, but no modification is recommended for persons with more modest renal dysfunction [1]. There is relatively little available information on TDF pharmacokinetics in patients with mild renal dysfunction and long-term use of the drug. A previous study [43] found that the median AUC was 1.41-fold higher in 10 HIV-uninfected individuals with a creatinine clearance from 50 to 79 ml/min per 1.73 m2 than in three individuals with creatinine clearance more than 80 ml/min per 1.73 m2 and another recent study demonstrated that higher TDF troughs are associated with renal impairment [44]. In the previously cited analysis in ACTG5208, women in the tenofovir/emtricitabine/lopinavir/RTV arm with lower prerandomization creatinine clearance were at the highest risk of developing renal insufficiency events [29].

Our findings are consistent with these reports, but the longitudinal nature of our cohort uniquely allowed us to model the effect of renal function prior to TDF initiation. We found that common factors can combine to significantly increase TDF levels and that mild renal impairment prior to TDF use can significantly impact subsequent TDF exposure. Of note, our models yielded similar findings when GFR was dichotomized to less than versus at least 80 or less than versus at least 90 ml/min per 1.73 m2 than when a GFR cut-off of less than 70 ml/min was used. These findings suggest that mild renal insufficiency prior to TDF use could result in a spiral of increased TDF exposure and subsequent renal injury. The recent trials that led to the approval of elvitegravir/cobicistat/TDF/emtricitabine as a single-pill combination excluded participants with estimated GFRs less than 70 ml/min per 1.73 m2 [45,46], limiting the generalizability of its findings to real-world HIV-infected populations in whom mild renal insufficiency is not uncommon [47–49], especially among women [50]. Adjustments of TDF dosing based on exposure measures could enhance the safety profile of this important medication.

The WIHS intensive pharmacokinetic studies demonstrate the feasibility and utility of measuring 12–24-h AUCs in large, unselected, and diverse populations under actual-use conditions to determine factors associated with exposure in the clinical setting. One limitation is that this study was performed exclusively in a cohort of women, and the results may not be directly applicable to HIV-infected men on TDF-based therapy. We also have not yet examined interpatient variability as a function of underlying host genetic characteristics, although such studies are underway. In spite of these limitations, there are several strengths to this study. Notably, there were a large number of individuals included in the analysis with longitudinal data collected over time, including renal function prior to the initiation of TDF-based cART. The study was also conducted under conditions that are representative of how antiretroviral medications are actually taken in routine practice. The study used a robust measure of tenofovir exposure as assessed by AUCs from intensive pharmacokinetic studies performed over 24 h. Finally, renal function was assessed both by cystatin-C and creatinine measures in our study.

In conclusion, concomitant RTV use, lower BMI, older age, and lower eGFR prior to starting TDF were all associated with higher TDF exposure in a cohort of HIV-positive women under conditions of routine clinical use. Estimates of GFR using cystatin C may enhance the evaluation of preexisting renal dysfunction on subsequent TDF exposure and were used in our models. Clinicians providing care to individuals with HIV should be aware of the impact of these common clinical conditions when prescribing TDF. More studies are needed to identify clinically relevant factors contributing to elevated TDF exposure, the pharmacodynamic relationship between exposure and adverse effects, as well as the genetic factors that may contribute to interpatient variability of antiretroviral concentrations in real-world practice.

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The authors would like to thank the WIHS participants who contributed to making this study possible. They also thank Ms Niloufar Ameli for her statistical programming.

S.B., R.M.G., P.B., R.S., H.M., Y.H., K.A., M.C., S.J.G., M.Y., M.G.S., and M.G. contributed to the design, analysis, and interpretation of the data, drafting and/or revising of the article. H.M., M.G., K.A., M.C., and M.Y. contributed to the acquisition of data. P.B., R.S., S.J.G., M.G.S., M.G., and R.M.G. contributed to the analysis and interpretation of data. Y.H. contributed to the plasma assay results. All authors contributed to the drafting or revising of the article and approved the final version of the article.

This work was supported by the National Institute of Allergy and Infectious Diseases (NIAID)/National Institutes of Health (NIH) (K23 A1067065 and RO1 AI098472 to M.G.). Additional funding is also provided by the National Center for Research Resources (NCRR)/NIH via the UCSF-CTSI (UL1 RR024131). Data in this study were collected by the Women's Interagency HIV Study (WIHS) Collaborative Study Group with centers (Principal Investigators) at New York City/Bronx Consortium (Kathryn Anastos); Brooklyn, NY (Howard Minkoff); Washington DC, Metropolitan Consortium (Mary Young); The Connie Wofsy Study Consortium of Northern California (Ruth Greenblatt); Chicago Consortium (Mardge Cohen); Data Coordinating Center (Stephen Gange). The WIHS is funded by NIAID (UO1-AI-35004, UO1-AI-31834, UO1-AI-34994, UO1-AI-34989, UO1-AI-34993, and UO1-AI-42590) and by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (UO1-HD-32632). The study is cofunded by the National Cancer Institute, the National Institute on Drug Abuse, and the National Institute on Deafness and Other Communication Disorders. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.

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Conflicts of interest

There are no conflicts of interest.

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areas under the concentration–time curve; cystatin C; diverse populations; exposure; glomerular filtration rate; HIV-infected women; pharmacokinetics; tenofovir

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