250 M. Fabbiani et al. / Pharmacological Research 63 (2011) 249–253 Since darunavir and raltegravir are metabolized through dis- mated from the analysis of 4 sets of 2 unknown samples of externaltinct metabolic pathways, a pharmacokinetic interaction between quality controls from the INSTAND e.V. (Düsseldorf, Germany)these two drug is not expected. However, unexpected drug–drug (WHO Collaborating Centre for Quality Assurance and Standard-interactions between antiretrovirals have already been reported ization in Laboratory Medicine), a quality control program for[10,11]. antiretroviral drugs. The aim of our study was to investigate potential interactions A single drug concentration value was used for each patient.between these two drugs in patients treated in the routine clinical For patients with multiple drug measurements available, thepractice. geometric mean concentration of the different samples was employed for comparisons. Inter-individual and intra-individual2. Materials and methods pharmacokinetic variability was evaluated through the coefﬁcient of variation (CVinter and CVintra , respectively), calculated as the2.1. Patients quotient of the standard deviation (SD) divided by the mean plasma concentration × 100. We enrolled HIV-infected patients on regimens containing a Since patients could be sampled over a 6 h period after dosingnucleoside/nucleotide reverse transcriptase inhibitors backbone (9–15 h), time-dependent drug elimination processes could haveplus darunavir/ritonavir 600/100 mg twice daily with (group 2) or exerted a large effect on darunavir concentration, thus introducingwithout (group 1) raltegravir 400 mg twice daily, that underwent a potential bias for the evaluation of results. To address this issue,measurement of plasma darunavir trough concentration (Ctrough , a sensitivity analysis was carried out, using a regression analysis12 ± 3 h after drug intake) during routine outpatient visits at three on the whole set of log-transformed concentration data with theclinical centres (Institute of Clinical Infectious Diseases, Catholic PrismTM software (GraphPad, San Diego, CA, USA), in order toUniversity of Sacred Heart, Rome, Italy; Department of Infectious estimate concentrations at a virtual sampling time of 12 h afterDiseases, University “La Sapienza”, Rome, Italy; Infectious Diseases last dosing.Unit, Spirito Santo Hospital, Pescara, Italy). In some patients, enfu-virtide was also co-administered. Only patients regularly attending 2.3. Statistical analysisthe planned visits and self-reporting regular intake of antiretro-viral doses in the last three days were included. Demographic, Categorical variables were compared with the 2 test or,clinical, laboratory variables and concomitant medications were when appropriate, the Fisher’s exact test; for continuous variables,registered for each patient at the time of drug level measurement. comparisons were based on the Student’s t-test (for unpaired sam-All patients at the clinical centres gave a written, informed consent ples). Kolmogorov–Smirnov test was used to verify if variablesto be included in observational studies. This informed consent was were ﬁtting a normal distribution. Factors potentially inﬂuencingapproved by the local institutional Ethics Committee. darunavir plasma levels (log10 transformed) were investigated by univariate and multivariate linear regression analysis. Spearman’s2.2. Drug measurements correlation coefﬁcients (r) were calculated to evaluate the correla- tion between concomitant darunavir and ritonavir concentration. Plasma samples were collected before the morning antiretrovi- A two-tailed p value of less than 0.05 was considered statisticallyral drug intake to measure Ctrough at steady state (at least two weeks signiﬁcant. All analyses were performed using the SPSS Version 13.0after starting last antiretroviral regimen): the time of the last drug software package (SPSS Inc, Chicago, IL).intake (obtained by patient self reporting) and of blood samplingwere recorded for each patient. Plasma darunavir and ritonavir 3. Resultslevels were measured by a validated HPLC-UV method (lowerlimit of quantiﬁcation 0.05 g/mL; overall inter-assay variability We analyzed 156 plasma samples obtained from 63 patients2.4–8.1% and intra-assay variability 2.3–5.9%; overall average accu- (44 in group 1 and 19 in group 2), whose main characteristics areracy 97–106%), slightly modiﬁed for the quantiﬁcation of darunavir reported in Table 1. A tenofovir-containing backbone was admin-[12,13]. The accuracy of the present method was repeatedly esti- istered in 79.4% (n = 50) of patients (81.8% in group 1 versus 73.7%Table 1Characteristics of the studied population. Total patients (n = 63) DRV + backbone (n = 44) Versus DRV + RAL + backbone (n = 19) p Male sex 46 (73) 31 (70.5) 15 (78.9) 0.552 Age, years* 46 (39–50) 45 (38–51) 47 (40–50) 0.949 Caucasian 55 (87.3) 39 (88.6) 16 (84.2) 0.688 Past injecting drug users 19 (30.2) 12 (27.3) 7 (36.8) 0.645 Past AIDS-deﬁning events 29 (46) 20 (45.5) 9 (47.4) 1.000 HBV/HCV co-infection 18 (28.6) 12 (27.3) 6 (31.6) 0.965 Time from starting ﬁrst cART regimen, years* 11.0 (9.5–12.2) 10.7 (9.5–11.4) 11.6 (8.1–12.4) 0.662 Time from starting current cART regimen, months* 4.7 (1.6–9.7) 4.3 (1.1–7.5) 4.9 (2.0–13.7) 0.099 Concomitant tenofovir 50 (79.4) 36 (81.8) 14 (73.7) 0.508 Concomitant enfuvirtide 5 (7.9) 5 (11.4) 0 (0) 0.311 CYP3A4 inducers usea 3 (4.8) 2 (4.5) 1 (5.3) 1.000 Acid reducing agents useb 1 (1.6) 1 (2.3) 0 (0) 1.000 Darunavir resistance mutationsc , * 1 (0–2) 0.5 (0–2) 1 (0–2) 0.376 Viral load, copies/mL* 49 (49–300) 62 (49–444) 49 (49–49) 0.543 CD4 cells count, cells/ L* 372 (212–563) 358 (226–442) 391 (150–614) 0.642Notes: values are expressed as n (%), except for * median (interquartile range).Abbreviations: DRV, darunavir; RAL, raltegravir; HBV, hepatitis B virus; HCV, hepatitis C virus; cART, combined antiretroviral therapy. a Phenobarbital or carbamazepine. b Proton pump inhibitors or H2 receptor antagonists. c Major plus minor, according to International AIDS Society list .
M. Fabbiani et al. / Pharmacological Research 63 (2011) 249–253 251in group 2, p = 0.508); enfuvirtide was co-administered to 5 (11.4%)patients in group 1 versus 0 in group 2 (p = 0.311). Three patients(two in group 1 and one in group 2) were concomitantly tak-ing cytochrome P450 inducers (phenobarbital or carbamazepine).Demographical and clinical characteristics of patients did not sig-niﬁcantly differ between the two groups. Overall, darunavir geometric mean Ctrough was 2.90 mg/L (95%conﬁdence intervals, 95% CI 2.34–3.60), while ritonavir geometricmean Ctrough was 0.21 mg/L (95% CI 0.17–0.27). Darunavir con-centration correlated with concomitant ritonavir levels (r = 0.476,p < 0.001). We observed a high inter-individual variability indarunavir plasma levels, both overall and in group 1 or 2 patients(CVinter 59%, 54% and 65%, respectively). Similarly, a high inter-individual variability was detected for ritonavir concentration(CVinter 103%, 103% and 87% in the whole population, in group 1and 2, respectively). Conversely, in the 34 patients (25 in group 1and 9 in group 2) with multiple samples available [median numberof samples per patient 3 (interquartile range, IQR 2–5)], intra-individual variability was more limited for both darunavir andritonavir [median darunavir CVintra 42% (IQR 15–54) and median Fig. 1. Darunavir plasma levels in patients concomitantly receiving or not receiv-ritonavir CVintra 47% (IQR 21–71)]. ing raltegravir. Notes: Squares represent geometric mean concentration, upper Ritonavir geometric mean concentration did not signiﬁcantly and lower whiskers represent 95% conﬁdence intervals. Abbreviations: DRV/rit, darunavir/ritonavir; RAL, raltegravir.differ between the two groups [0.25 mg/L (95% CI 0.19–0.32) versus0.16 mg/L (95% CI 0.10–0.25), p = 0.229]. On the contrary, patients ingroup 1 had a higher darunavir geometric mean concentration than ing for time from last drug intake and concomitant drugsthose in group 2 [3.44 mg/L (95% CI 2.79–4.23) versus 1.95 mg/L used.(95% CI 1.19–3.20), p = 0.017] (Fig. 1). However, the proportion of The results were conﬁrmed also when the analysis wassubjects with concomitant HIV-RNA < 50 copies/mL was higher in restricted to a more homogeneous population, represented onlygroup 2 (78.9% versus 47.7%, p = 0.028). by patients taking a tenofovir-containing backbone and not con- Darunavir levels were not signiﬁcantly inﬂuenced by tenofovir comitantly receiving enfuvirtide, cytochrome P450 inducers andco-administration [geometric mean 2.88 mg/L (95% CI 2.21–3.75) acid reducing agents: darunavir geometric mean concentration waswith tenofovir versus 2.96 mg/L (95% CI 2.25–3.91) without teno- 3.63 mg/L (95% CI 2.85–4.63) in group 1 versus 1.80 mg/L (95% CIfovir, p = 0.919]. 0.94–3.42) in group 2, p = 0.019; in multivariate linear regression We investigated factors potentially inﬂuencing darunavir analysis, after adjusting for time from last drug intake, the mean dif-plasma levels by a linear regression model (Table 2). At uni- ference (95% CI) in darunavir concentration was −0.30 log10 mg/Lvariate analysis, only raltegravir co-administration was related to (95% CI −0.55/−0.04) (p = 0.022) in patients concomitantly receiv-lower darunavir plasma levels (mean difference −0.25 log10 mg/L, ing raltegravir as compared to those not receiving raltegravir.95% CI −0.45/−0.05, p = 0.017). Co-administration of enfuvir- To test the hypothesis that darunavir plasma levels tended totide, acid reducing agents or cytochrome P450 inducers did not decrease in the allowed time-frame of 9–15 h after dosing, a regres-seem to signiﬁcantly inﬂuence darunavir concentration in this sion analysis was performed on the whole set of log-transformedpopulation, although the small number of patients receiving data. In spite of the fact that the majority of measurementsthese drugs limits the value of this observation. In a multi- were obtained from patients sampled in the interval 11–13 hvariable model, raltegravir co-administration was independently after dosing (mean ± standard deviation: 11.82 ± 1.30, coefﬁcientrelated to a lower darunavir concentration (mean difference of variation = 11.03%), the regression analysis indeed revealed that−0.25 log10 mg/L, 95% CI −0.46/−0.04, p = 0.020) after adjust- darunavir concentration decreased in a linear manner (Fig. 2),Table 2Factors inﬂuencing darunavir plasma concentration (log10 transformed, uni- and multivariate linear regression model). Variable Univariate analysis Multivariate analysis Mean difference (95% CI) in p value Mean difference (95% CI) in p value DRV concentration (log10 mg/L) DRV concentration (log10 mg/L) Sex (female versus male) 0.12 (−0.09; 0.34) 0.264 Caucasian ethnicity 0.05 (−0.25; 0.33) 0.759 Age (per 10 years more) 0.06 (−0.06; 0.18) 0.297 Weight (per 10 kg more) −0.01 (−0.08; 0.06) 0.737 Injecting drug users 0.03 (−0.18; 0.24) 0.763 HBV or HCV coinfection 0.07 (−0.14; 0.28) 0.508 Renal impairment 0.31 (−0.13; 0.76) 0.166 Concomitant raltegravir use −0.25 (−0.45; −0.05) 0.017 −0.25 (−0.46; −0.04) 0.020 Concomitant tenofovir use −0.01 (−0.25; 0.22) 0.919 −0.05 (−0.29; 0.19) 0.687 Concomitant enfuvirtide use −0.06 (−0.42; 0.29) 0.722 −0.15 (−0.51; 0.21) 0.415 Use of cytochrome CYP3A4 inducersa −0.08 (−0.53; 0.38) 0.738 −0.16 (−0.70; 0.39) 0.561 Concomitant acid reducing agents useb 0.13 (−0.64; 0.91) 0.729 0.21 (−0.72; 1.15) 0.647 Time from last drug intake (per hour longer) −0.05 (−0.13; 0.04) 0.273 −0.04 (−0.13; 0.04) 0.318Abbreviations: CI, conﬁdence intervals; DRV, darunavir; HBV, hepatitis B virus; HCV, hepatitis C virus. a Phenobarbital or carbamazepine. b Proton pump inhibitors or H2 receptor antagonists.
252 M. Fabbiani et al. / Pharmacological Research 63 (2011) 249–253 3 harbouring a virus partially resistant to darunavir, in the case of a dual therapy with raltegravir and darunavir/ritonavir or in case of a g/L) lower darunavir dosing such as those used in once daily approaches rations (Ln mg 2 with darunavir/ritonavir 800/100 mg. Our ﬁnding is quite unexpected, since these two compounds are lasma DRV 1 believed to be metabolized by distinct pathways. The mechanism D at the basis of this interaction remains therefore unclear and needs 0 adequate investigations. Given the distinct metabolic pathways, an 9 10 11 12 13 14 15 16 interaction at the CYP isoenzyme level is unlikely. concentr Pl -1 Garvey et al. analyzed changes in the pharmacokinetic proﬁle of darunavir/ritonavir 800/100 mg once daily during a stepwise -2 consecutive switch from nucleos(t)ide-based to a raltegravir- c containing and nucleos(t)ide-sparing regimen : no signiﬁcant changes of darunavir pharmacokinetic parameters were found -3 10 days after adding raltegravir, while darunavir Ctrough was signiﬁcantly reduced 10 days later, after discontinuing teno- Hours from last dosing fovir/emtricitabine. This ﬁnding was interpreted as an effect ofFig. 2. Regression analysis of ln-transformed darunavir concentration data. Abbrevi- tenofovir discontinuation, on the basis of a previously reportedations: DRV, darunavir. Notes: A total of 156 plasma samples obtained by 63 patients increased darunavir exposure with concomitant tenofovir .were used for the regression analysis. However, on the basis of our results, also raltegravir could have played a role in the decrease of darunavir exposure. Indeed, inthe decrease being directly related to the time from last drug Garvey’s study, darunavir Ctrough showed a mean, not signiﬁcantdosing. The regression line which best ﬁtted the data had a reduction of 13% after addition of raltegravir: the short duration ofslope = −0.167 ± 0.057 and an X-intercept = 19; the slope was sig- this co-administration (10 days) and the small sample size (n = 14),niﬁcantly different from zero (p = 0.004). Having obtained such could have reduced the sensitivity to detect a signiﬁcant inter-equation, an adjustment of data to a virtual sampling time of 12 h action. We hypothesize that the signiﬁcant effect found 10 daysafter last drug dosing was carried out on the raw data set and a new later, after nucleos(t)ide reverse transcriptase inhibitors discontin-statistical analysis was performed. Results of this sensitivity analy- uation, in that study, could not only have resulted from tenofovirsis conﬁrmed the hypothesis of the interaction between darunavir discontinuation, but also from a later effect of raltegravir addition.and raltegravir: darunavir geometric mean concentration was Interestingly, in our series the effect of raltegravir on darunavir3.39 mg/L (95% CI 2.74–4.19) in group 1 versus 1.99 mg/L (95% CI levels appeared to be independent from the concomitant adminis-1.24–3.21) in group 2, p = 0.023; in multivariate linear regression tration of tenofovir.analysis, after adjusting for concomitant drugs used, the mean dif- The potential for an interaction between raltegravir and pro-ference in darunavir concentration was −0.25 log10 mg/L (95% CI tease inhibitors had been already demonstrated in the case of−0.46/−0.04) (p = 0.021) when raltegravir was co-administered. atazanavir: Zhu et al. showed a reduction in atazanavir exposure In support of this interaction, we also report the case of 3 when it was coadministered unboosted at a dose of 300 mg twicepatients among those analyzed where darunavir levels where mea- daily with raltegravir 400 mg twice daily in healthy subjects .sured before and after intensiﬁcation of a darunavir-based regimen Recent studies suggest that raltegravir could be a sub-with raltegravir. In two patients darunavir trough concentration strate/inhibitor of P-glycoprotein (Pgp), an efﬂux pump expresseddecreased by 51.1% (from 2.62 to 1.28 mg/L) and 41.5% (from 3.95 on the surface of many cell types [18,19]. As a consequence, theto 2.31 mg/L), respectively; in a third patient the decrease was mini- hypothesis of an interaction between darunavir and raltegravir atmal (4.9%: from 4.52 mg/L to 4.30 mg/L) and could also be explained this level could be plausible.by intra-individual variability. Since this is a cross-sectional observational study performed in the routine clinical outpatient setting, some limitations should be4. Discussion recognized and our results should be interpreted with caution since inter-individual variability could have played a role in our ﬁndings. HIV-infected patients receiving darunavir 600 mg with ritona- However, we have also observed a decrease in darunavir levels invir 100 mg twice daily concomitantly receiving raltegravir 400 mg three longitudinally analyzed subjects who added raltegravir totwice daily showed a signiﬁcantly lower plasma darunavir Ctrough a darunavir-based regimen. Another possible limitation could beas compared to patients not receiving raltegravir. Results were represented by the lack of a standardized adherence monitoring,not inﬂuenced by the concomitant administration of tenofovir and usually not performed in routine clinical practice, that could havewere conﬁrmed by several sensitivity analyses. To the best of our inﬂuenced the results. However, it should be noted that subjectsknowledge, this is the ﬁrst report supporting a potential drug with lower darunavir levels had a higher proportion of HIV-RNAinteraction between darunavir and raltegravir. This interaction did below 50 copies/mL, making a lower adherence behaviour in thisnot appear to be virologically signiﬁcant in the studied popula- group of patients highly unlikely.tion, since a higher proportion of subjects with viral load below In conclusion, a potential drug interaction between darunavir50 copies/mL was found in the group concomitantly receiving the and raltegravir was observed. Although this did not seem virologi-two drugs, in agreement with the results of the BENCHMRK trials, cally signiﬁcant in our population, it should be taken into accountwhere a signiﬁcant proportion of patients receiving darunavir with in speciﬁc settings where it could be particularly relevant to obtainraltegravir plus optimized background therapy achieved virological a high darunavir plasma concentration. The reported ﬁndings needsuppression . In this observational study we could only analyze to be conﬁrmed by adequately designed prospective studies.the Ctrough levels and could not perform a more complete phar-macokinetic analysis. However, Ctrough levels may be predictive of Fundingtreatment efﬁcacy. It remains to be determined, if the observedreduction in darunavir exposure may become clinically signiﬁcant This work was supported by Istituto Superiore di Sanità,in the setting of selected highly treatment-experienced patients Ministero della Salute, Programma Nazionale AIDS, grants n 50F.10,
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