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Antimicrobial Agents and Chemotherapy, December 2002, p. 3907-3916, Vol. 46, No. 12
0066-4804/02/$04.00+0 DOI: 10.1128/AAC.46.12.3907-3916.2002
Copyright © 2002, American Society for Microbiology. All Rights Reserved.
Stanford University School of Medicine, Stanford, California,1 University of California, San Diego, San Diego, California,2 Global Pharmaceutical Research and Development, Abbott Laboratories, Abbott Park, Illinois,3 Johns Hopkins School of Medicine, Baltimore, Maryland,4 Southwestern Medical School, University of Texas, Dallas, Texas5
Received 21 May 2002/ Returned for modification 8 August 2002/ Accepted 12 September 2002
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0.5 log10 copies/ml. Of these subjects, 82% (14 of 17) whose viruses had three or fewer protease inhibitor mutations and 88% (14 of 16) whose viruses had an indinavir virtual phenotypic susceptibility test of more than sixfold less than that for the baseline isolate were considered virologic responders. The indinavir virtual inhibitory quotient, which is a function of baseline indinavir phenotypic resistance (estimated by virtual phenotype) and the indinavir predose concentration in plasma achieved with indinavir-ritonavir combination therapy, was the best predictor of a viral load reduction. Sixteen subjects discontinued the study by week 48 due to adverse events, predominantly related to hyperlipidemia. Pharmacokinetic intensification of indinavir-based therapy with ritonavir reduced the viral loads in subjects but added toxicity. The virtual inhibitory quotient, which incorporates both baseline viral resistance and the level of drug exposure in plasma, was superior to either baseline resistance or drug exposure alone in predicting the virologic response. |
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Ritonavir is a licensed HIV PI that is also a very potent inhibitor of cytochrome P450 3A4 (CYP3A4). Coadministration of ritonavir with other PIs increases the bioavailabilities and half-lives of the PIs by inhibiting CYP3A4-mediated metabolism (8, 13). Addition of ritonavir to indinavir-containing regimens may have several potential advantages. In particular, this combination can be administered without the food restrictions required with indinavir as a single PI-based regimen and can be administered twice a day (BID) as opposed to three times a day (TID) (11; A. Hsu, G. R. Granneman, M. Heath-Chiozzi, E. Ashbrenner, L. Manning, R. Brooks, P. Bryan, K. Erdman, and E. Sun, Program Abstr. 12th Int. AIDS Conf., abstr. 22361, 1998). When ritonavir at 400 mg BID is administered with indinavir at 400 mg BID, the pharmacokinetic parameters for indinavir are differentially altered compared to those for indinavir administered at 800 mg TID: the indinavir Cmaxs are reduced by 50%, while the indinavir Ctoughs are increased nearly fourfold and the areas under the plasma concentration-time curves (AUCs) remain unchanged (11). Furthermore, the interpatient variabilities of indinavir pharmacokinetic parameters are substantially reduced with ritonavir coadministration (11).
This study was designed to evaluate the safety, tolerability, and efficacy of pharmacokinetic intensification or boosting of indinavir-based therapy with ritonavir in subjects who were receiving indinavir therapy and in whom HIV RNA was detectable in plasma. Ctroughs of PIs have been associated with virologic suppression in several clinical studies (1, 5, 6, 9, 15), as have AUCs in other studies (1, 14). Enhancement of indinavir Ctroughs by the addition of ritonavir to the antiretroviral drug regimen could theoretically enhance virologic suppression. Furthermore, the differential alteration of indinavir pharmacokinetic parameters by ritonavir in this particular regimen could help to discriminate which of these parameters are more closely associated with in vivo PI activity. Finally, the study design also allowed assessment of the degree of indinavir resistance that could be overcome with pharmacokinetic boosting.
(This study was presented in part at the 7th Conference on Retroviruses and Opportunistic Infections, San Francisco, Calif., 30 January to 2 February 2000 [N. Shulman et al., 7th Conf. Retrovir. Opportunistic Infect., abstr. 534, 2000]; the 4th International Workshop on HIV Drug Resistance and Treatment Strategies, Sitges, Spain, 12 to 16 June 2000 [A. Zolopa et al., 4th Int. Workshop on HIV Drug Resist. Treatment Strategies, abstr. 95, 2000]; the 13th World AIDS Conference, Durban, South Africa, July 2000 [D. Havlir et al., 13th Int. AIDS Conf., abstr. WePeB4122, 2000]; the 8th Conference on Retroviruses and Opportunistic Infections, Chicago, Ill., 4 to 8 February 2001 [A. Hsu et al., 8th Conf. Retrovir. Opportunistic Infect., abstr. 337, 2001; D. Kempf et al., 8th Conf. Retrovir. Opportunistic Infect., abstr. 523, 2001]; and the 2nd International Workshop on Clinical Pharmacology of HIV Therapy, Noordwijk, The Netherlands, 2 to 4 April 2001 [A. Hsu et al., 2nd Int. Workshop Clin. Pharmacol. HIV Ther., abstr. 7.3, 2001].)
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Subjects were switched from 800 mg of indinavir TID to 400 mg of indinavir BID and 400 mg of ritonavir BID. The dose of ritonavir was introduced at 200 mg BID for the first 2 days, escalated to 300 mg BID for the next 3 days, and then further escalated to 400 mg BID, as tolerated. This dose escalation schedule could have been lengthened to 10 days in the case of tolerability-related events. Reduction of the ritonavir dose to 300 mg BID was permitted for subjects who were unable to tolerate 400 mg of BID. On day 1 of the study, the food restrictions and fluid intake recommended with indinavir therapy were removed. In order to determine the isolated effect of ritonavir-mediated alteration of indinavir pharmacokinetics on virologic suppression, no other changes in the subjects' antiretroviral regimens were permitted during the first 3 weeks. After week 3, subjects were permitted to change the NRTI portion of their antiretroviral regimen at the discretion of their physicians. The study design is shown in Fig. 1.
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FIG. 1. Study design. RTV, ritonavir; IDV, indinavir; PK, pharmacokinetic.
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For all subjects, indinavir Ctroughs were measured at the baseline, week 3, and week 24. Intensive pharmacokinetic profiling was performed for a subset of 16 subjects at the baseline and week 3. At the baseline, these subjects received 800 mg of indinavir with water after an overnight fast and were then given a standardized breakfast 2 h later. Plasma indinavir levels were measured at time zero (predosing) and at 1, 1.5, 2, 3, 4.5, 6, and 8 h postdosing. At week 3, these same subjects received observed doses of 400 mg of indinavir and 400 mg of ritonavir at the time of a standardized breakfast. Indinavir and ritonavir levels were measured at time zero (predosing) and at 2, 4, 6, 8, 10, and 12 h postdosing. Subjects received their NRTIs at the same time that they received the indinavir and ritonavir doses. The meals and snacks given after breakfast were not standardized or restricted.
The plasma indinavir and ritonavir concentrations were measured by previously validated reverse-phase high-performance liquid chromatography procedures with UV detection at 205 nm and a modified mobile phase (11). The lower limits of quantitation for the assay are 2 ng/ml for indinavir with 0.5 ml of plasma and 6 ng/ml for ritonavir with 1 ml of plasma. The assay is linear between 2 and 400 ng/ml for indinavir and 6 and 3,500 ng/ml for ritonavir. Samples quantified above the highest standard were diluted with blank plasma and reassayed. The following pharmacokinetic parameters were evaluated: AUC, the minimum concentration in plasma (Cmin), Cmax, and Ctrough.
Baseline genotypic analysis was performed for all subjects. HIV RNA was extracted from plasma, and nested PCR amplification was used to generate a 1.3-kb fragment encompassing Pr and the first 900 nucleotides of RT (18). Direct dideoxynucleotide terminator cycle sequencing of the PCR product was performed as described previously (18). Sequencing of both strands was performed. Sequencing reactions were analyzed on an ABI 377 instrument (Perkin-Elmer Applied Biosystems, Foster City, Calif.) and manually proofread and edited. Sequences were compared with the HIV type 1 (HIV-1) clade B consensus sequence, and differences in amino acid sequences, including positions that contained a mixture of wild-type and mutant residues, were classified as mutations. RT codons 1 to 300 and Pr codons 1 to 99 were analyzed. Mutations at the following amino acids in HIV Pr were classified as PI mutations according to the Data Analysis Plan of the HIV Resistance Collaborative Working Group (3): 10, 20, 24, 30, 32, 33, 36, 46, 47, 48, 50, 54, 71, 73, 77, 82, 84, 88, and 90. Mutations observed at the following amino acids in RT were classified as major NRTI mutations: 41, 67, 69, 70, 75, 151, 184, 210, 215, and 219.
HIV phenotyping was performed with plasma obtained at the baseline by the Antivirogram method (Tibotec-Virco, Mechelen, Belgium) (10). Phenotypic data were expressed as the fold change in the IC50, which was calculated by dividing the IC50 of the drug for the recombinant virus (containing the HIV Pr and RT genes of the baseline patient plasma sample) by the IC50 of the drug for the standard wild-type recombinant virus.
Virtual phenotype (VP) values were calculated from the entire Pr and RT sequences through a proprietary method by Tibotec-Virco (B. Larder, S. Kemp, and K. Hertogs, Program Abstr. 4th Int. Workshop HIV Drug Resist. Treatment Strategies, abstr. 63, 2000). Briefly, this method involves comparison of the Pr or RT sequence to matching sequences in a large database of sequences for isolates for which both the genotype and the phenotype have been determined. The VP is the ratio of the average IC50 for the isolates with the corresponding genotypic matches in the Virco database divided by the IC50 for the wild-type virus. This method gives a reasonable estimate of the fold change in IC50 for a given genotype compared to the IC50 for the wild type. The VP may then be applied to the IC50s for wild-type virus determined under specific conditions, such as serum-adjusted IC50s, to estimate the IC50s for other viruses in the presence of human serum.
The inhibitory quotient (IQ) characterizes the relationship between drug exposure and drug susceptibility (7). For each sample for which baseline VP and week 3 Ctroughs were available, virtual IQs (vIQs) for indinavir and ritonavir were calculated by the following formula: Ctrough at week 3/(VP x serum-adjusted IC50 for wild-type virus).The serum-adjusted IC50s of indinavir and ritonavir were calculated as the mean IC50 of each drug for three wild-type laboratory strains (strains pNL4-3, HXB2, and HIV-1IIIB) as determined in side-by-side experiments in the presence of 50% human serum and 10% fetal calf serum. The serum-adjusted IC50s of indinavir and ritonavir obtained by this method are 0.053 and 0.96 µg/ml, respectively (16).
Statistical analysis. All statistical analyses were performed with the SAS system (release 6.12; SAS Institute Inc., Cary, N.C.). All statistical tests were two tailed and were performed at the 0.05 level of statistical significance unless specified otherwise. Changes in the indinavir pharmacokinetic results from the baseline (indinavir at 800 mg TID) to week 3 (indinavir at 400 mg BID and ritonavir at 400 mg BID) were evaluated by a paired t test. In addition, the association between phenotype and VP (for indinavir and ritonavir), the association between the number of PI mutations and the indinavir VP, the association between Ctrough and VP (for indinavir and ritonavir), and the association between the indinavir vIQ and the ritonavir vIQ were evaluated by using the Spearman rank correlation coefficient (r).
Virologic response was defined as achieving a viral load below the limit of quantitation (i.e., <50 copies/ml) or achieving a viral load reduction from that at the baseline of at least 0.5 log10 copies/ml. Response was analyzed by using the dropouts-as-censored method, in which data for subjects who discontinued treatment as responders are censored, while those who discontinued treatment as nonresponders are counted as nonresponders for the duration of the study. Virologic response was stratified by the number of baseline PI mutations (
3,
4), the number of baseline RT mutations (
3,
4), the indinavir VP (<6-fold, >6-fold), the indinavir Ctrough at week 3 (<0.75 µg/ml, >0.75 µg/ml), and the indinavir vIQ (<2, >2). Between-stratum comparisons were performed by Fisher's exact test.
Logistic regression was used to evaluate the virologic response as a function of the baseline viral load, baseline genotypic and phenotypic resistance parameters, and week 3 indinavir pharmacokinetic parameters. In particular, stepwise logistic regression was used to evaluate the association between virologic response and potential predictors of virologic response including baseline viral load, number of PI mutations, number of RT mutations, indinavir VP, indinavir Ctrough at week 3, fold change in indinavir Ctrough between the baseline and week 3, and vIQ (for indinavir or ritonavir). The stepwise logistic regression was performed by using entry and exit significance levels of 0.10. In addition, all independent (predictor) variables with the exception of the number of PI mutations and the number of RT mutations were transformed (log10) prior to performance of the stepwise logistic regression.
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Study population. Thirty-seven male subjects were included in the study. The median age of the subjects was 42 years. Twenty-five subjects were white, five were black, six were Hispanic, and one was Asian. Prior antiretroviral treatment, including indinavir exposure, was extensive. In particular, subjects had previously received a median of 34.6 months (range, 5.8 to 43.8 months) of indinavir treatment and a median of 71.1 months (range, 19.2 to 239.1 months) of antiretroviral therapy. The subjects had a median baseline CD4 cell count of 325 cells/µl (range, 28 to 1,372 cells/µl) and a median HIV RNA level of 3.3 log10 copies/ml (range, 1.7 to 4.8 log10 copies/ml). The majority of subjects (81%; 30 of 37) had baseline plasma HIV RNA levels of <10,000 copies/ml, with 24% (9 of 37) having baseline HIV RNA levels between 50 and 400 copies/ml. Baseline characteristics are summarized in Table 1.
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TABLE 1. Baseline characteristics and resistance
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FIG. 2. Baseline prevalence of mutations.
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FIG. 3. Relationship between phenotype and VP.
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0.001 for both comparisons). The AUC at 24 h (AUC24) for indinavir did not change significantly, decreasing by 18% (P = 0.061). These pharmacokinetic changes in HIV-infected subjects were similar to those previously observed in healthy volunteers (11). |
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TABLE 2. Indinavir pharmacokinetics at baseline (indinavir TID) and week 3 (indinavir and ritonavir BID)a
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FIG. 4. Indinavir Ctroughs following the change from indinavir at 800 mg TID to ritonavir at 400 mg BID and indinavir at 400 BID. *, the 50% effective concentration (EC50) is from the Crixivan package insert (Merck & Co., Inc.); C0, predose concentration.
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FIG. 5. vIQ range. RTV, ritonavir; IDV, indinavir.
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FIG. 6. Overall response rates obtained by the dropouts-as-censored (DAC) and intent-to-treat (ITT) methods
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TABLE 3. Predictors of response
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The baseline indinavir VP was found to be associated with virologic responses at week 3 and week 24. We found that 88% (14 of 16) of subjects with baseline indinavir VPs less than sixfold were virologic responders at week 3, whereas 33% (5 of 15) with baseline indinavir VPs more than sixfold were virologic responders at week 3 (P = 0.003). Similarly, 77% (10 of 13) of subjects with baseline indinavir VPs less than sixfold were virologic responders at week 24, whereas 20% (3 of 15) with baseline indinavir VPs more than sixfold were virologic responders at week 24 (P = 0.007). However, the difference between subjects with baseline indinavir VPs less than sixfold and those with indinavir VPs more than sixfold at week 48 (60% [6 of 10 subjects] versus 20% [3 of 15 subjects]) was no longer statistically significant (P = 0.087). No subject with baseline indinavir VPs
12-fold responded to intensification of indinavir therapy with ritonavir.
Higher indinavir Ctroughs at week 3 were found to be associated with virologic responses at weeks 24 and 48. In particular, 77% (10 of 13) of subjects with an indinavir Ctrough >0.75 µg/ml were considered virologic responders at week 24, whereas 14% (2 of 14) of subjects with indinavir Ctroughs <0.75 µg/ml were considered virologic responders at week 24 (P = 0.002). Similarly, 70% (7 of 10) of subjects with indinavir Ctroughs >0.75 µg/ml were considered virologic responders at week 48, whereas 7% (1 of 14) with indinavir Ctroughs <0.75 µg/ml were considered virologic responders at week 48 (P = 0.002).
The indinavir vIQ, which is a function of both the week 3 indinavir Ctrough and the baseline indinavir VP, appears to be the best predictor (of the parameters evaluated) of virologic response in this study. At week 3, 89% (16 of 18) of subjects with an indinavir vIQ >2 were considered virologic responders, whereas 11% (1 of 9) of subjects with an indinavir vIQ <2 were considered virologic responders (P < 0.001). Similar results were observed at week 24 (75% [12 of 16 subjects] versus 0% [0 of 9 subjects]; P < 0.001) and week 48 (62% [8 of 13 subjects] versus 0% [0 of 9 subjects]; P = 0.006).
As the ritonavir vIQ was highly correlated with the indinavir vIQ (rho = 0.89), it was not possible to differentiate between the association of the virologic response with the indinavir vIQ and the virologic response with the ritonavir vIQ. A stepwise logistic regression analysis was conducted at weeks 3, 24, and 48, with virologic response as the dependent variable and the following parameters as potential predictor (independent) variables: baseline viral load (log10 transformed), indinavir vIQ (log10 transformed), indinavir VP, the number of PI mutations, the number of NNRTI mutations, the indinavir Ctrough at week 3 (log10 transformed), and the fold change in Ctrough between the baseline and week 3 (log10 transformed), all as continuous variables. Of the independent variables considered for inclusion in the model, only indinavir vIQ entered the model at week 3 (intercept = -2.154; P = 0.012) and week 24 (intercept = -2.925; P = 0.009) (Table 4). At week 48, none of the independent variables was found to be associated with a virologic response (P > 0.10); however, this result may have been due to the small sample size at week 48. In a separate analysis, the ritonavir vIQ (log10 transformed) was substituted for the indinavir vIQ (log10 transformed). At week 3, the indinavir VP was the only significant predictor of viral response (intercept = 2.168; P = 0.015); however, the ritonavir vIQ was the only significant predictor of the viral response at week 24 (intercept = -1.675; P = 0.020). None of the independent variables was found to be associated with a virologic response at week 48 (P > 0.10).
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TABLE 4. Multiple stepwise logistic regression analysis of virologic response
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FIG. 7. Comparison of indinavir (IDV) VP and indinavir vIQ.
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TABLE 5. Adverse events and laboratory abnormalitiesa
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The second key finding of this study is the demonstration of the predictive value of the vIQ above and beyond that provided by resistance testing. The vIQ, a ratio that takes into consideration both the baseline resistance and the indinavir trough concentrations achieved with combination therapy, was the best predictor of a virologic response. A previous study with Pr inhibitor-experienced subjects found that IQ is better at predicting the virologic response to lopinavir- and ritonavir-based therapy than pharmacokinetic measurements alone are (D. J. Kempf, A. Hsu, J. Isaacson, P. Jiang, S. Brun, C. Renz, G. R. Granneman, and E. Sun, Program Abstr. 2nd Int. Workshop Clin. Pharmacol. HIV Ther., abstr. 7.3, 2001). In the present study, the vIQ was used due to the number of baseline samples that had HIV RNA levels too low to be analyzed for isolate phenotype; the isolates could, however, be analyzed for their genotypes. VPs were highly correlated to actual phenotypes both in the subjects whose isolates' phenotypes were analyzed in this study and in a cross-sectional study of a large database (Larder et al., Program Abstr. 4th Int. Workshop HIV Drug Resist. Treatment Strategies, abstr. 63, 2000); therefore, vIQ is likely to be a reasonable proxy for IQ.
As seen in a study with healthy volunteers (11), administration of indinavir at 400 mg BID with ritonavir at 400 mg BID enhanced the indinavir Ctrough and reduced the indinavir Cmax without altering the AUC. While previous studies have shown the cross-sectional association of the virologic response with a higher Ctrough (1, 5, 6, 9, 15), the discrimination of Ctrough, Cmax, and AUC as pharmacodynamic predictors for PI activity is generally not feasible due to the correlation between these parameters. This is the first longitudinal study to demonstrate that the Ctrough is associated with the in vivo antiviral activities of PIs, independent of Cmax and AUC.
One potential limitation to this study is that pharmacologically active doses of ritonavir were administered, which may have contributed to the virologic suppression. However, the majority of samples analyzed had ritonavir vIQs of <1 (Fig. 5). Furthermore, the ritonavir and indinavir vIQs were highly correlated, and the median indinavir vIQ was >20-fold higher than that of ritonavir. On the basis of the results of this pharmacodynamic analysis, it is likely that the increased potency observed in this study can be largely, if not exclusively, attributed to indinavir. This is supported by the results of the stepwise regression analysis, in which the indinavir vIQ was a stronger predictor of response than the ritonavir vIQ. The association of the week 24 response obtained with the ritonavir vIQ when the indinavir vIQ was excluded from the model is likely to represent a surrogate for the stronger association with indinavir vIQ.
Pharmacokinetic enhancement in this study came at a cost of substantial toxicity. More than half of the subjects discontinued therapy due to adverse events related to ritonavir or increased indinavir exposure, or both. Kidney stones were rare at these doses, supporting the hypothesis that nephrolithiasis and the nephropathy of indinavir are related to the Cmax (4). Identification of the optimal doses of indinavir and ritonavir required to maximize antiretroviral activity yet minimize toxicity when the drugs are used in combination requires further exploration.
In the clinical setting, measurement of Ctroughs of drugs, in addition to performance of resistance testing, may be useful for maximizing patient responses to PI-based therapies. Future studies, including studies with other PIs, are needed to confirm these findings.
This study was supported in part by NIH grant M01 RR 00070. Funding for this study was obtained from Abbott Laboratories (study M98-985). A.H., C.R., S.B., P.J., R.R. D.J.K. and E.S. are employees of Abbott Laboratories. Other than study support, the remaining authors (N.S., A.Z., D.H., J.G., and E.R.) received no other financial support from the sponsor.
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