Factors Associated with Daily Tenofovir Exposure in Thai Subjects Taking Combination Antiretroviral Therapy

Abstract

Tenofovir (TFV) exposure is associated with antiretroviral efficacy and risk of kidney disease. There is evidence of high interindividual variability of the pharmacokinetics of TFV. The effect of several clinical conditions on the pharmacokinetics of TFV has been observed and may partly explain its variability. We assessed factors influencing the pharmacokinetics of TFV in Thai patients. Thirty participants (50% female) taking efavirenz- or ritonavir-boosted protease inhibitor-based regimens were investigated. Intensive pharmacokinetic sampling was performed over 24 h. Multivariate geometric mean regression models adjusted for covariates with p≤0.2 in univariate analysis were developed. The median age was 41 years. Five participants [three taking a protease inhibitor (PI) and two taking efavirenz (EFV)] had mild renal dysfunction [estimated glomerular filtration rate (eGFR) 60–90 ml/min/1.73 m²; range 72–89]. TFV AUC_0–24 was 23% (95% CI 1–49%; p=0.04) higher in those taking PI vs. EFV, 39% (95% CI 5–84%; p=0.02) higher in those with mild renal dysfunction, and reduced by 16% (95% CI 5–26%; p=0.008) with each 10 kg body weight increase, after adjusting for sex and duration of TFV exposure. In PI-treated subjects TFV AUC_0–24 increased by 3% (0.3–6%; p=0.03) for each mg·h/liter increase in ritonavir (RTV) AUC_0–24 after adjusting for sex, weight, mild renal impairment, and proximal renal tubular dysfunction. Significantly higher TFV exposures were independently associated with PI regimens, mild renal impairment, lower body weight, and increasing RTV AUC_0–24. Clinicians should be aware of the effect of these factors on TFV exposure when this drug is prescribed.

Introduction

Tenofovir (TFV) is one of the most widely used antiretroviral agents worldwide, recommended as a choice in first line combination antiretroviral regimens (cART) in both resource-rich and resource-limited settings for adults and adolescents initiating treatment.^1,2 Tenofovir diproxil fumarate (TDF) is an oral prodrug of TFV. It is converted to TFV after absorption through the gut and first past metabolism through the liver. Within cells, TFV is rapidly phosphorylated to tenofovir diphosphate (TFV-DP), which is the active form. TFV is mainly excreted unchanged into urine by glomerular filtration and active tubular secretion.³ Although TFV is usually well tolerated, TFV-induced renal toxicity has been reported.⁴

The mechanism of TFV-induced renal dysfunction involves damage to the proximal renal tubular cells, but the precise mechanisms mediating the toxicity are unclear.⁵ Previous studies demonstrated that TFV concentrations and cumulative duration of TFV exposure are found to be associated with an increased risk of kidney disease.^6

–9 Higher TFV trough concentrations were found in subjects with renal dysfunction.^6
–8 This supports the hypothesis that TFV concentrations may play a part in the development of renal toxicity through chronic exposure to higher TFV concentrations.

Along with TFV exposure, recent studies have shown that concomitant treatment with protease inhibitors (PIs) boosted with ritonavir (RTV) and lower body weight are independent risk factors for TFV-associated renal dysfunction.^7,10 The efficacy of TFV was mainly established in combination with efavirenz, but TFV dosed concomitantly with boosted PIs but not efavirenz results in higher TFV exposure, which may have little benefit in terms of efficacy, but serves to increase a person's risk of renal toxicity.¹¹ Asians may be at particularly high risk for renal complications with TFV treatment because of their low body mass index and body weight.¹⁰ Thai patients have higher concentrations of a number of antiretroviral agents than Western counterparts, at least in part explained by their lower body weight.¹² In a recent meta-analysis, the greatest mean difference in calculated creatinine clearance between TFV-treated subjects and the comparator group was noted in a study in which the subjects were Japanese, although the confidence intervals were wide.¹³ Therefore, the lower body weight of the patients in this population could lead to a higher TFV concentration, ultimately increasing the risk of developing TFV toxicity.

High interindividual variability of TFV pharmacokinetics has been observed,¹⁴ and body weight, renal function, and comedications can influence TFV pharmacokinetics.^11,14,15 Although factors contributing to interindividual variability of TFV pharmacokinetics have been extensively investigated in other ethnicities,^14
–16 none of the studies was performed in an Asian population. Identifying factors influencing TFV concentrations in Asians could be useful for adjusting TFV dosage regimens to obtain optimal therapeutic effects while preventing toxicities related to high TFV concentrations.

In this study we identified factors influencing daily TFV exposure, assessed as the AUC_0–24, and other pharmacokinetic parameters including C _max and C _24h, in Thai subjects taking efavirenz (EFV) or RTV-boosted PI-based cART.

Materials and Methods

This was a cross-sectional, intensive pharmacokinetic (PK) study conducted at the HIV Netherlands Australia Thailand Research Collaboration (HIV-NAT) in Bangkok, Thailand. The study was approved by the Chulalongkorn University Institutional Review Board, and all subjects gave written informed consent.

Pharmacokinetic sampling and pharmacokinetic assay

HIV-1-infected adult Thai patients (over 18 years of age) who had been taking 300 mg TDF qd with EFV qd, lopinavir/RTV bid, or atazanavir/RTV qd for at least 6 months and had plasma HIV RNA <50 copies/ml were studied. Subjects were asked to take cART in the morning for 2 weeks before the intensive PK sampling day. On that day, medication intake was observed by a study nurse, and blood sampling was performed at time=0 (predose) and at 1, 2, 4, 6, 8, 10, 12, and 24 h postdosing. A physical examination was also conducted and routine clinical chemistry and hematology laboratory analyses were performed. Plasma was transferred to a polypropylene tube and stored at −20°C (for no longer than 1 month) and then at −80°C until analysis.

Plasma concentrations of TFV were determined by a validated high-performance liquid chromatography (HPLC) assay with fluorescence detection and a lower limit of quantification of 0.015 mg/liter.¹⁷ The TFV calibration curve was linear over the concentration range of 0.015 to 1.5 mg/liter, and within-run and between-run percent variation was <10%. In subjects taking RTV-boosted lopinavir or atazanavir, RTV concentrations were determined using HPLC with fluorescence detection. The lower limit of quantification was 0.045 mg/liter.¹⁸ The within-run and between-run variation was <10% and the accuracy was between 95% and 105%. As an external quality control measure, the HIV-NAT laboratory participates in an International program for therapeutic drug monitoring of antiretroviral drugs in plasma.¹⁹

Statistical analyses

PK parameters for TFV and RTV were calculated by noncompartmental methods using WinNonLin (version 5.2, Pharsight Corporation, Mountain View, CA). The following parameters were calculated for TFV: area under the plasma concentration-time 0–24 h (AUC_0–24), the maximum plasma concentration (C _max), the trough plasma concentration at 24 h (C ₂₄), the time to reach the maximum plasma concentration (T _max), the apparent elimination half-life (t _1/2), the apparent clearance (CL/F), and the apparent volume of distribution (V _d/F). In subjects taking RTV-boosted lopinavir or atazanavir, we calculated the RTV AUC_0–12 or AUC_0–24, respectively.

Estimated glomerular filtration rate (eGFR) was calculated by the Modification of Diet in Renal Disease (MDRD) equation with Thai racial correction factor (eGFR-Th), developed to accurately assess GFR in a Thai population.²⁰ Body surface area was calculated according to the formula of Dubois.²¹ Proximal renal tubular dysfunction (PRTD) was defined as at least two of the following five criteria: (1) fractional tubular absorption of phosphorus <0.80 or tubular maximum phosphorus corrected for GFR <2.6 mg/dl; (2) total urinary phosphorus excretion >1,200 mg/day; (3) fractional excretion of uric acid >15%; (4) β₂-microglobulin >1 mg/day or β₂-microglobulin/urinary creatinine >0.3 mg/liter; and (5) nondiabetic glucosuria (urine glucose >300 mg/day or positive urine glucose) with normal glycemia (plasma glucose <100 mg/dl).

Statistical analyses were performed using Stata version 12 (Statacorp, College Station, TX). Demographic characteristics of subjects taking EFV- and PI-based regimens were compared using a Wilcoxon test for continuous covariates and a chi-square or Fisher's exact test as appropriate for categorical covariates. The geometric mean (GM) and percentage coefficient of variation (%CV) and the mean (SD) or the median (IQR) of TFV PK parameters were calculated for subjects on EFV- and PI-based regimens; T _max was reported as the median (IQR). Regression models were used to assess how the TFV AUC_0–24, C _max, and C _min GM were influenced by factors including regimen type (PI or EFV), age, body weight, gender, hepatitis B positive, mild renal dysfunction (eGFR-Th=60–90 ml/min/1.73 m²), PRTD, duration of TFV exposure, and total duration of ART exposure. Factors significant at p≤0.2 in univariate analysis were adjusted for in a multivariate model. Since an aim of the project was to compare PK parameters in subjects taking PI- or nonnucleoside reverse transcriptase inhibitor (NNRTI)-based regimens, regimen was included in all multivariate models regardless of the significance level in univariate analysis.

A secondary analysis was conducted in subjects taking PI-based regimens to examine the effect of RTV AUC_0–24 on TFV AUC_0–24, C _max, and C ₂₄. In subjects taking bid PI regimens, the RTV AUC_0–12 was doubled to derive the AUC_0–24.

Results

Thirty participants (50% female) with a median age of 41(IQR 38–49; range 30–57) years were studied; the sample size was empirical. One subject taking a PI-based regimen was enrolled, but was excluded from analysis because their weight and height (102 kg and 185 cm, respectively) were not representative of the normal Thai population. Subjects were taking EFV 600 mg once daily (qd) (n=14), lopinavir/RTV 400/100 mg twice daily (bid) (n=12), or atazanavir/RTV (ATV/r) 300/100 mg qd (n=4). There were no significant differences in patient characteristics noted between the PI and EFV groups except for eGFR-Th and total duration of ART use, which was significantly lower in the EFV group (Table 1). Five participants (three taking PI and two taking EFV) had mild renal dysfunction (eGFR-Th 60–90 ml/min/1.73 m²; range 73–89); the median (IQR) duration of TFV exposure was 4.2 (3.8–5.1) years in these participants vs. 3.0 (2.1–4.0) years in those with normal renal function (p=0.1) and the median (IQR) duration of ART therapy was 11.1 (6.5–13.0) years in those with mild renal dysfunction vs. 7.7(5.1–11.2) years in those with normal renal function (p=0.5). One of these subjects with mild renal dysfunction did not have urinalysis conducted, and therefore we were unable to establish whether this subject had RPTD; eGFR in 3/30 subjects with PRTD ranged from 96 ml/min/1.73 m² to 146 ml/min/1.73 m². TFV plasma concentration time curves for subjects taking EFV and PI regimens, by whether subjects had mild renal dysfunction, are shown in Fig. 1.

FIG. 1.

Mean tenofovir (TFV) plasma versus time concentrations by whether the subject has an estimated glomerular filtration rate (eGFR) of 70–90 ml/min/1.73 m².

Table 1.

Demographic Characteristics of Subjects Taking Tenofovir Diproxil Fumerate with Efavirenz or Protease Inhibitor-Based Regimens

Covariate ^a	PI (N=16)	EFV (N=14)	Total (N=30)	p^a
Age (years)	40 (36–48)	43.5 (39–50)	41 (38–49)	0.39
Male:female, n (%)	8 (50):8 (50)	7 (50):7 (50)	15 (50):15 (50)	1.00
Height (cm)	160 (156–170)	164 (158–170)	163 (157–170)	0.49
Weight (kg)	63.4 (56.1–70.2)	55.2 (53.4–68.5)	61.6 (53.5–71.0)	0.33
BSA (m²)	1.63 (1.55–1.79)	1.62 (1.55–1.75)	1.63 (1.57–1.76)	0.62
Hepatitis B positive	2 (13)	4 (29)	6 (20)	0.38
Proximal tubular dysfunction, n (%)	2 (13)	1 (7)	3 (10)	1.00
Serum creatinine (mg/dl)	0.75 (0.65–0.8)	0.8 (0.7–0.9)	0.8 (0.7–0.9)	0.22
eGFR-Th (ml/min/1.73 m²)	119 (100–127)	104 (94–112)	110 (96–121)	0.05
Mild renal dysfunction,^b n (%)	3 (19)	2 (14)	5 (17)	1.00
Duration of cART (years)	10.8 (7.3–13.7)	5.3 (3.8–10.6)	8.4 (5.1–12.7)	0.01
Duration of TDF treatment (years)	3.1 (2.1–4.9)	3.8 (2.1–4.8)	3.6 (2.1–4.8)	0.90

Categorical covariates are presented as n (%) and continuous covariates are presented as median (IQR). Significance tests were by Wilcoxon test for continuous covariates and Chi-square or Fisher's exact test as appropriate for categorical covariates.

eGFR 60–90 ml/min/m² by MDRD-Thai.

PI, protease inhibitor; EFV, efavirenz; BSA, body surface area; eGRF-Th, estimated glomerular filtration rate-Thai; cART, combination antiretroviral therapy; TDF, tenofovir diproxil fumerate.

Geometric means (%CV) of TFV AUC_0–24, C _max, and C ₂₄ were 3,517 (31) ng·h/ml, 406 (49) ng/ml, and 70 (34) ng/ml, respectively, in subjects taking PI regimens, and 3,045 (32) ng·h/ml, 402 (33) ng/ml, and 60 (37) ng/ml, respectively, in those taking EFV (Table 2). The median time to maximum plasma concentration was 1 h in 83% of participants and 2 h in the remaining 17%.

Table 2.

Tenofovir Diprozil Fumerate Pharmacokinetic Parameters by Drug Group

Parameter	PI (n=16)	EFV (n=14)	Total (n=30)
TFV AUC_0–24 (ng·h/ml)
Geometric mean (%CV)	3,517 (31)	3,045 (32)	3,288 (32)
Arithmetic mean (SD)	3,675 (1,163)	3,177 (925)	3,443 (1071)
TFV C _max (ng/ml)
Geometric mean (%CV)	406 (49)	402 (33)	404 (42)
Arithmetic mean (SD)	443 (175)	422 (135)	433 (155)
TFV C _24h (ng/ml)
Geometric mean (%CV)	70 (34)	60 (37)	65 (36)
Arithmetic mean (SD)	74 (25)	64 (29)	69 (27)
TFV half-life (h)
Geometric mean (%CV)	12.4 (24)	11.5 (23)	12.0 (23)
Arithmetic mean (SD)	12.7 (2.76)	11.8 (2.62)	12.3 (2.68)
TFV clearance (liters/h)
Geometric mean (%CV)	85 (31)	95 (27)	88 (30)
Arithmetic mean (SD)	89 (28)	98 (28)	93 (28)
TFV volume of distribution (liters)
Geometric mean (%CV)	1,482 (30)	1,579 (40)	1,527 (35)
Arithmetic mean (SD)	1,543 (450)	1,713 (854)	1,622 (663)
TFV T _max (h)
Median (IQR)	1 (1–1)	1 (1–1)	1 (1–1)
RTV AUC_0–24 (mg·h/liter)
Geometric mean (%CV)	9.8 (39)
Arithmetic mean (SD)	10.6 (4.4)

PI, protease inhibitor; EFV, efavirenz; TFV, tenofovir; RTV, ritonavir.

The univariate and multivariate regression models for TFV AUC_0–24, C _max, and C ₂₄ are shown in Table 3. In multivariate models, after adjusting for sex and duration of TVF exposure, the TFV AUC_0–24 GM was 23% (95% CI 1–49%) higher in subjects taking PI-based regimens vs. EFV, 39% (95% CI 5–84%) higher in those with mild renal dysfunction vs. normal renal function, and reduced by 16% (95% CI 5–26%) for a 10 kg increase in body weight.

Table 3.

Univariate and Multivariate Regression Models for Geometric Mean Ratio of Tenofovir AUC_0–24, C _max, and C ₂₄

	Univariate		Multivariate
	GMR (95% CI)	p	GMR (95% CI)	p
TFV AUC_0–24 (ng·h/ml)
PI vs. EFV	1.16 (0.92–1.45)	0.21	1.23 (1.01–1.49)	0.04
PRTD	1.25 (0.88–1.77)	0.21
Mild renal dysfunction^a	1.35 (1.01–1.82)	0.05	1.39 (1.05–1.84)	0.02
Female vs. male	1.20 (0.95–1.50)	0.12	1.00 (0.81–1.23)	0.97
Age (years)	1.00 (0.99–1.02)	0.77
Hepatitis B positive	1.11 (0.83–1.49)	0.46
Weight (per 10 kg increase)	0.87 (0.77–0.99)	0.04	0.84 (0.74–0.95)	0.008
Duration of ART (years)	1.01 (0.98–1.03)	0.67
Duration of TDF therapy (years)	1.07 (1.00–1.04)	0.04	1.03 (0.97–1.09)	0.29
TFV C _max (ng/ml)
PI vs. EFV	1.01 (0.74–1.37)	0.95	0.98 (0.74–1.30)	0.89
PRTD	1.53 (0.96–2.46)	0.07	1.64 (1.01–2.69)	0.05
Mild renal dysfunction^a	1.25 (0.84–1.86)	0.27
Female vs. male	1.23 (0.92–1.65)	0.16	1.21 (0.88–1.65)	0.22
Age (years)	0.99 (0.97–1.01)	0.49
Hepatitis B positive	1.14 (0.78–1.67)	0.48
Weight (per 10 kg increase)	0.83 (0.71–0.98)	0.03	0.92 (0.77–1.10)	0.33
Duration of ART (years)	1.00 (0.96–1.03)	0.81
Duration of TDF therapy (years)	1.08 (1.00–1.17)	0.06	1.06 (0.98–1.15)	0.11
TFV C₂₄ (ng/ml)
PI vs. EFV	1.17 (0.91–1.51)	0.21	1.26 (0.99–1.60)	0.06
PRTD	1.14 (0.76–1.71)	0.52
Mild renal dysfunction^a	1.21 (0.86–1.71)	0.27
Female vs. male	1.22 (0.95–1.57)	0.11	1.12 (0.87–1.42)	0.37
Age (years)	1.00 (0.98–1.02)	0.88
Hepatitis B positive	0.88 (0.64–1.22)	0.44
Weight (per 10 kg increase)	0.86 (0.75–0.99)	0.04	0.85 (0.74–0.98)	0.03
Duration of ART (years)	1.00 (0.97–1.03)	0.87
Duration of TDF therapy (years)	1.03 (0.96–1.11)	0.36
TFV AUC_0–24 (ng·h/ml) in subjects taking RTV-boosted PI regimens
PRTD	1.33 (0.88–2.00)	0.16	1.35 (0.92–1.98)	0.11
Mild renal dysfunction^a	1.33 (0.89–1.99)	0.15	1.30 (0.93–1.82)	0.10
Female vs. male	1.25 (0.91–1.71)	0.15	1.10 (0.83–1.45)	0.46
Age (years)	0.99 (0.97–1.01)	0.41
Hepatitis B positive	1.18 (0.71–1.95)	0.49
Weight (per 10 kg increase)	0.83 (0.69–1.00)	0.05	0.88 (0.74–1.04)	0.11
Duration of ART (years)	0.98 (0.94–1.03)	0.49
Duration of TDF therapy (years)	1.05 (0.97–1.14)	0.21
RTV AUC_0–24 (mg·h/liter)	1.04 (1.01–1.07)	0.03	1.03 (1.003–1.06)	0.03

Mild renal dysfunction: eGFR with Thai racial correction=60–90 liters/min/1.73 m²

GMR, geometric mean ratio; TFV, tenofovir; PI, protease inhibitor; EFV, efavirenz; PRTD, proximal renal tubular dysfunction; ART, antiretroviral therapy; TDF, tenofovir diproxil fumerate; RTV, ritonavir.

The TFV C _max geometric mean ratio (GMR) was approximately 1, and not significantly different in subjects taking PI-based vs. EFV-based regimens. The TFV C _max GM was 64% (95% CI 1–269%) higher in participants with proximal renal tubular dysfunction after adjusting for regimen, sex, weight, and duration of TDF exposure. The TFV C ₂₄ GM was reduced by 15% (95% CI 2–26%) for a 10 kg increase in body weight after adjusting for regimen and sex. The GM of TFV C ₂₄ was on average 26% higher in subjects taking PI-based regimens in adjusted models, but this was not statistically significant.

In subjects taking PI-based regimens, the GM (%CV) for the RTV AUC_0–24 was 9.8 (39) mg·h/liter. In a multivariate TFV AUC_0–24 GM model, after adjusting for mild renal dysfunction, PRTD, sex, and weight, a 1 mg·h/liter increase in RTV AUC_0–24 increased the TVF AUC_0–24 GM by 3% (95% CI 0.3–6%). A higher, but not significant TFV C _max and C ₂₄ GM were observed with increasing RTV AUC_0–24 in univariate models (data not shown).

Discussion

Although intracellular concentrations of TFV-DP contribute to the drug's efficacy, there is evidence of a relationship between TFV concentrations in plasma and viral suppression.^8,9,22,23 The use of TFV plasma concentrations as monitoring parameters for efficacy and safety could be convenient in clinical practice. Our study found a high interindividual variability of TFV exposure and pharmacokinetics (Table 2). Several factors may influence TFV exposure including body size, renal function, comedications, and age.^14,15,24 Therefore, identifying factors that may impact TFV exposure are important for TFV dose adjustment. Currently, information regarding demographic variables and how they influence exposure to TFV is limited, especially in Asian populations.

TFV is primarily excreted unchanged in the urine through a combination of glomerular filtration and active tubular secretion. Therefore, that renal function influences TVF exposure is expected, and is confirmed by the results of our study. We found that the TFV AUC_0–24 increased by 39% among patients with mild renal dysfunction (eGFR 60–90 ml/min/1.73 m²). However, the decrease in renal function did not affect TFV C _max and C ₂₄. This finding is consistent with a previous study showing that TFV AUC_0–∞ slightly increased in subjects with mild renal impairment (CLcr 50–80 ml/min) whereas no differences in C _max, T _max, and elimination half-life were observed.²⁵ Moreover, the results from previous population pharmacokinetic studies of TFV demonstrate a strong relationship between the ratio of body weight to serum creatinine (BW/Scr) and TFV clearance.^14,15 Interestingly, the estimated GFR (calculated by the Cockcroft and Gault equation) was not a significant covariate for TFV clearance in these studies.

Several surrogate markers have been used to represent renal function including serum creatinine, BW/Scr, and eGFR. In our study, renal function was estimated using eGFR estimated by the MDRD equation with the Thai racial correction factor.²⁰ This equation takes age, sex, and race into account and therefore should more accurately estimate renal function in our study population. Even though TFV dose adjustments are not required in patients with mild renal dysfunction, TFV concentrations should be closely monitored. Our results also demonstrated that PRTD was significantly associated with TFV C _max, but not with TFV AUC_0–24 and C ₂₄. This discordancy could be due to the small number of patients with PRTD in our study, and therefore there is insufficient power to detect its effect on TFV AUC_0–24.

Body size is one important factor influencing a drug's exposure. Our study demonstrated an inverse relationship between TFV AUC_0–24 and body weight. A 10 kg weight increase resulted in a 26% reduction in TFV AUC_0–24. Similarly, previous studies have shown that various measures of body size, including body mass index (BMI) and body weight, are correlated with TFV exposure.^14
–16 A study found a 1.04-fold increase of TFV AUC_0–24 with each 10% decrease in BMI, and the risk of TFV-associated nephrotoxicity was more evident in patients with lower body weight.^10,16 Therefore, patients with smaller body size, who potentially have a higher degree of drug exposure, could experience more severe toxicities.^10,26 In general, Asians, including Thais, have lower body sizes compared with other ethnicities. Thus, close monitoring of TFV exposure and renal function in this population is warranted.

TFV is not a substrate of cytochrome enzymes and therefore has a low potential for drug–drug interactions, but an interaction between TFV and other antiretroviral drugs including lopinavir/RTV has been demonstrated.^11,15,16,27 A 24–50% increase in TFV AUC, coadministered with lopinavir/RTV or atazanavir, was reported in previous pharmacokinetic studies.^3,27,28 Our results also confirmed the influence of concomitant use of RTV on TFV exposure. In the group of patients taking PI-based regimens, each mg·h/liter increase in RTV AUC_0–24 resulted in a 3% higher TFV AUC_0–24, after adjusting for mild renal dysfunction, PRTD, sex, and weight.

Although the exact mechanism of this interaction is still unclear, one possible mechanism could be due to inhibition of efflux transporters by RTV. RTV is a potent inhibitor of efflux transporters, including P-glycoprotein and multidrug-resistant proteins (MRPs) found in the intestine, kidney, and liver,^29

–33 which suggests that the mechanisms could involve interactions in the intestine and kidney. In vitro, PIs inhibit intestinal efflux pumps leading to a decrease in TDF efflux and, thus, an increase in TDF absorption.³⁴ Interestingly, the results from our study demonstrated that TFV C _max was similar between patients taking PI-based and EFV-based regimens. Therefore, if the interaction between PI and TFV is through an inhibition of intestinal efflux pump, it is possible that the concomitant use of PIs may affect the extent rather than the rate of TFV absorption.

Another possible mechanism explaining the increase in TFV AUC_0–24 by RTV could be an inhibition of efflux transporters in the kidney. Kiser et al. demonstrated a 17.5% decrease in TFV renal clearance when lopinavir/RTV was coadministered.¹¹ Elimination of TFV into the urine requires drug transporters including organic anion transporters (OATs), MRP2, and MRP4.^35

–38 Inhibition of these transporters in the proximal tubule cells by RTV or lopinavir/RTV could result in decreased TFV clearance, leading to higher TFV exposure. Based on the available data in our study, the precise mechanism of the interaction between PIs and TFV cannot be determined and requires further investigation.

There are some limitations to our study. First, due to a small number of patients with PRTD, the influence of PRTD on TFV exposure could not be reliably estimated. Second, there is evidence that genetic variation in TFV transporters may influence TFV pharmacokinetics and renal toxicities.^11,39 These genetic variations may partly explain the interindividual variability of TFV exposure, but were not investigated in this study. Third, due to the cross-sectional nature of our study, we were unable to establish whether mild renal function caused higher TVF exposure or whether the cumulative exposure to higher TFV AUC led to a reduction in eGFR. Lastly, the number of patients taking RTV-boosted PI regimens was small (N=16), and limits the power for statistical tests in our secondary analysis.

Despite these limitations, we are not aware of other studies that have investigated factors influencing TFV exposure, assessed by AUC_0–24, in Thai patients. As such, our results provide useful evidence to guide clinicians taking care of HIV patients receiving TDF, particularly when Thailand has implemented guidelines for treating HIV regardless of CD4 count, and TDF is a first line agent.⁴⁰ Accordingly, concomitant use of RTV-boosted PIs, body weight, and the impact of renal function on TFV exposure should be considered when clinicians prescribe TDF for Thai and other Asian patients. In some adult patients who are at risk of having higher TFV concentrations, there may be a case for using TDF tablet strengths of 200 mg or 250 mg, which have recently been marketed for pediatric use, although they are not currently available in Thailand.

In summary, significantly higher daily TFV exposures were independently associated with mild renal impairment, lower weight, and higher RTV AUC_0–24 in those taking RTV-boosted PI. Renal function in patients taking TFV should be carefully monitored once their eGFR falls below 90 ml/min/1.73 m². Moreover, all patients with low body weight receiving RTV-containing cART should be carefully monitored, since they may have higher TFV exposures and may be more prone to renal toxicity.

Footnotes

Acknowledgments

We would like to thank the patients for their participation in this study and the HIV-NAT staff. This study was funded by the National Research Council of Thailand (NRCT) under Grant PorKor/2554-136, the Thailand Research Fund (TRF) under Grant RSA5380002, the Ratchadapisek Sompotch Endowment Fund, Faculty of Medicine, Chulalongkorn University under Grant RA33/53, and the Aligning Care and Prevention of HIV/AIDS with Government Decentralization to Achieve Coverage and Impact: ACHIEVED Project (Global Fund Thailand).

This study was presented at the 24th Conference of the Australasian Society of HIV Medicine (ASHM), Melbourne, Australia, October 17–19, 2012.

Author Disclosure Statement

No competing financial interests exist. KR is partly supported by the Senior Research Scholar, Thai Research Fund (TRF) and the National Research University Project of CHE (HR1164A).

References

Panel on Antiretroviral Guidelines for Adults and Adolescents: Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Available at http://aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL.pdf: Department of Health and Human Services. Accessed February 12, 2013 .

WHO: Antiretroviral therapy for HIV infection in adults and adolescents: recommendations for a public health approach—2010 rev: World Health Organization, 2010. Accessed February 12, 2013 .

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