The use of drug resistance algorithms and genotypic inhibitory quotient in prediction of lopinavir–ritonavir treatment response in human immunodeficiency virus type 1 protease inhibitor-experienced patients

Therapeutic drug monitoring of antiretroviral drugs in HIV-infected patients

INTRODUCTION

Therapeutic drug monitoring (TDM) may be beneficial when applied to antiretroviral (ARV). Even though TDM can be a valuable strategy in HIV management, its role remains controversial. Areas covered: This review provides a comprehensive update on important issues relating to TDM of ARV drugs in HIV-infected patients. Articles from PubMed with keywords relevant to each topic section were reviewed. Search strategies limited to articles published in English. Expert commentary: There is evidence supporting the use of TDM in HIV treatment. However, some limitations need to be considered. The evidence supporting the use of routine TDM for all patients is limited, as it is not clear that this strategy offers any advantages over TDM for selected indications. Selected groups of patients including patients with physiological changes, patients with drug-drug interactions or toxicity, and the elderly could potentially benefit from TDM, as optimized dosing is challenging in these populations.

Comparable long-term efficacy of Lopinavir/Ritonavir and similar drug-resistance profiles in different HIV-1 subtypes

BACKGROUND

Analysis of potentially different impact of Lopinavir/Ritonavir (LPV/r) on non-B subtypes is confounded by dissimilarities in the conditions existing in different countries. We retrospectively compared its impact on populations infected with subtypes B and C in Israel, where patients infected with different subtypes receive the same treatment.

METHODS

Clinical and demographic data were reported by physicians. Resistance was tested after treatment failure. Statistical analyses were conducted using SPSS.

RESULTS

607 LPV/r treated patients (365 male) were included. 139 had HIV subtype B, 391 C, and 77 other subtypes. At study end 429 (71%) were receiving LPV/r. No significant differences in PI treatment history and in median viral-load (VL) at treatment initiation and termination existed between subtypes. MSM discontinued LPV/r more often than others even when the virologic outcome was good (p = 0.001). VL was below detection level in 81% of patients for whom LPV/r was first PI and in 67% when it was second (P = 0.001). Median VL decrease from baseline was 1.9±0.1 logs and was not significantly associated with subtype. Median CD4 increase was: 162 and 92cells/µl, respectively, for patients receiving LPV/r as first and second PI (P = 0.001), and 175 and 98, respectively, for subtypes B and C (P<0.001). Only 52 (22%) of 237 patients genotyped while under LPV/r were fully resistant to the drug; 12(5%) were partially resistant. In48%, population sequencing did not reveal resistance to any drug notwithstanding the virologic failure. No difference was found in the rates of resistance development between B and C (p = 0.16).

CONCLUSIONS

Treatment with LPV/r appeared efficient and tolerable in both subtypes, B and C, but CD4 recovery was significantly better in virologically suppressed subtype-B patients. In both subtypes, LPV/r was more beneficial when given as first PI. Mostly, reasons other than resistance development caused discontinuation of treatment.

Can linear regression modeling help clinicians in the interpretation of genotypic resistance data? An application to derive a lopinavir-score

BACKGROUND

The question of whether a score for a specific antiretroviral (e.g. lopinavir/r in this analysis) that improves prediction of viral load response given by existing expert-based interpretation systems (IS) could be derived from analyzing the correlation between genotypic data and virological response using statistical methods remains largely unanswered.

METHODS AND FINDINGS

We used the data of the patients from the UK Collaborative HIV Cohort (UK CHIC) Study for whom genotypic data were stored in the UK HIV Drug Resistance Database (UK HDRD) to construct a training/validation dataset of treatment change episodes (TCE). We used the average square error (ASE) on a 10-fold cross-validation and on a test dataset (the EuroSIDA TCE database) to compare the performance of a newly derived lopinavir/r score with that of the 3 most widely used expert-based interpretation rules (ANRS, HIVDB and Rega). Our analysis identified mutations V82A, I54V, K20I and I62V, which were associated with reduced viral response and mutations I15V and V91S which determined lopinavir/r hypersensitivity. All models performed equally well (ASE on test ranging between 1.1 and 1.3, p = 0.34).

CONCLUSIONS

We fully explored the potential of linear regression to construct a simple predictive model for lopinavir/r-based TCE. Although, the performance of our proposed score was similar to that of already existing IS, previously unrecognized lopinavir/r-associated mutations were identified. The analysis illustrates an approach of validation of expert-based IS that could be used in the future for other antiretrovirals and in other settings outside HIV research.

[Evidence-based therapeutic drug monitoring of lopinavir]

The HIV protease inhibitor lopinavir presents a wide inter-individual variability related to liver and intestinal metabolism involving CYP3A. Published studies were analyzed to establish whether there is evidence that therapeutic drug monitoring of lopinavir could improve patient care. In naïve or pretreated HIV-infected patients, no relationship could be evidenced between virological efficacy and trough lopinavir concentration, most likely because concentrations are above inhibitory concentrations. Although data are limited, patients with elevated triglycerides and cholesterol had trough lopinavir concentrations >8 000 ng/mL. These data suggest that the level of evidence of interest of lopinavir therapeutic drug monitoring is may be recommended in some situations such as children, pregnant women, pretreated patients if the number of mutations is <5, when coadministration with drug with metabolizing enzyme inducing properties is warranted and toxicity.

The benefit of simplification from tipranavir/ritonavir 500/200 bid to 500/100 bid guided by therapeutic drug monitoring

Despite being among the most potent protease inhibitors, the use of tipranavir (TPV) is hampered by a high pill burden and frequent side effects compared with other boosted protease inhibitors. A total of 10 patients receiving TPV/ritonavir (TPV/RTV) 500/200 for longer than 6 months were randomized to stay on the same dosing schedule or switch to TPV/RTV 500/100. Although all patients on TVP/RTV 500/200 remained stable for the next 12 weeks, 3 out of 5 patients who switched doses experienced benefits in terms of reducing aminotransferases and total cholesterol. Fasting triglycerides were also reduced in 2 of them. Plasma HIV-RNA remained undetectable in all patients, despite the observed decline in TPV trough concentrations.

Inhibitory quotient in HIV pharmacology

PURPOSE OF REVIEW

This review discusses the use of the inhibitory quotient in light of therapeutic drug monitoring of antiretroviral drugs. The inhibitory quotient is a parameter that combines viral resistance data with drug exposure data, and has its main role in therapeutic drug monitoring of protease inhibitors in experienced patients. Data from recent clinical studies investigating inhibitory quotient cutoffs to be used in therapeutic drug monitoring will be reviewed. In addition points for discussion regarding the use and study of inhibitory quotients will be presented.

RECENT FINDINGS

A number of studies generated data on the use of the inhibitory quotient in general and the genotypic inhibitory quotient in particular. Most of these studies define a cutoff inhibitory quotient value, above which the virological response rate is higher. These cutoff values can be used in therapeutic drug monitoring and give guidance to the clinician on dose adjustments. Genotypic inhibitory quotient cutoff values are available for amprenavir, atazanavir, darunavir, lopinavir, saquinavir and tipranavir.

SUMMARY

The inhibitory quotient is becoming a valuable tool in therapeutic drug monitoring. At this moment most data are available for the genotypic inhibitory quotient. Nevertheless, a consensus needs to be reached on a number of items, including the methods to study inhibitory quotient as well as the mathematical and virological background.

Use of different inhibitory quotients to predict early virological response to tipranavir in antiretroviral-experienced human immunodeficiency virus-infected patients

Information about the relationship between pharmacological parameters and an early virological response to tipranavir (TPV) is scarce. Human immunodeficiency virus (HIV)-infected patients who had received TPV as part of a salvage regimen were analyzed retrospectively. A virological response was defined as a decline in the HIV RNA level of > or = 1 log unit or to <50 copies/ml between weeks 4 and 12 of therapy. The virtual inhibitory quotient (vIQ) was calculated as the ratio of the TPV plasma trough concentration (C(trough))/virtual change in the 50% inhibitory concentration. Three genotypic inhibitory quotients (gIQs) were calculated by using different TPV resistance mutation scores (from the International AIDS Society-USA [IAS-USA], Randomized Evaluation of Strategic Intervention in Multidrug-Resistant Patients with Tipranavir [RESIST], and Agence Nationale de Recherches sur le Sida et les Hépatites Virales [ANRS] trials). The sensitivities, specificities, positive predictive values (PPVs), negative predictive values (NPVs), and likelihood ratios for a positive result (LHR+) and a negative result (LHR-) [LHR+ = sensitivity/(1-specificity); LHR- = (1-sensitivity)/specificity] were calculated. A total of 57 HIV-infected patients were analyzed. A virological response was achieved by 77% of the patients. TPV resistance mutations, TPV C(trough), vIQs, and gIQs were all significantly associated with a virological response. The vIQ had the best PPV and NPV (97% and 78%, respectively). The values of the LHR+ were 7.8 for vIQ, 3.4 for the RESIST gIQ, 3.3 for the IAS-USA gIQ, 3.1 for the ANRS gIQ, 2.2 for TPV C(trough), and 1.3 for the IAS-USA and RESIST scores. The values of LHR- were 0 for the RESIST score, 0.07 for vIQ, 0.09 for the IAS-USA score, 0.27 for the RESIST gIQ, 0.32 for the IAS-USA gIQ, 0.37 for the ANRS gIQ, and 0.48 for TPV C(trough). HIV-infected patients who initiate a salvage regimen based on TPV may benefit from baseline drug resistance testing and TPV plasma concentration determination, as vIQ is the best predictor of a virological response.

Antiretroviral drug resistance testing in adult HIV-1 infection: 2008 recommendations of an International AIDS Society-USA panel

Resistance to antiretroviral drugs remains an important limitation to successful human immunodeficiency virus type 1 (HIV-1) therapy. Resistance testing can improve treatment outcomes for infected individuals. The availability of new drugs from various classes, standardization of resistance assays, and the development of viral tropism tests necessitate new guidelines for resistance testing. The International AIDS Society-USA convened a panel of physicians and scientists with expertise in drug-resistant HIV-1, drug management, and patient care to review recently published data and presentations at scientific conferences and to provide updated recommendations. Whenever possible, resistance testing is recommended at the time of HIV infection diagnosis as part of the initial comprehensive patient assessment, as well as in all cases of virologic failure. Tropism testing is recommended whenever the use of chemokine receptor 5 antagonists is contemplated. As the roll out of antiretroviral therapy continues in developing countries, drug resistance monitoring for both subtype B and non-subtype B strains of HIV will become increasingly important.

Pharmacokinetics of high-dose lopinavir-ritonavir with and without saquinavir or nonnucleoside reverse transcriptase inhibitors in human immunodeficiency virus-infected pediatric and adolescent patients previously treated with protease inhibitors

Human immunodeficiency virus (HIV)-infected children and adolescents who are failing antiretrovirals may have a better virologic response when drug exposures are increased, using higher protease inhibitor doses or ritonavir boosting. We studied the pharmacokinetics and safety of high-dose lopinavir-ritonavir (LPV/r) in treatment-experienced patients, using an LPV/r dose of 400/100 mg/m(2) orally every 12 h (p.o. q12h) (without nonnucleoside reverse transcriptase inhibitor [NNRTI]), or 480/120 mg/m(2) p.o. q12h (with NNRTI). We calculated the LPV inhibitory quotient (IQ), and when the IQ was <15, saquinavir (SQV) 750 mg/m(2) p.o. q12h was added to the regimen. We studied 26 HIV-infected patients. The median age was 15 years (range, 7 to 17), with 11.5 prior antiretroviral medications, 197 CD4 cells/ml, viral load of 75,577 copies/ml, and a 133-fold change in LPV resistance. By treatment week 2, 14 patients had a viral-load decrease of >0.75 log(10), with a median maximal decrease in viral load of -1.57 log(10) copies/ml at week 8. At week 2, 19 subjects showed a median LPV area under the concentration-time curve (AUC) of 157.2 (range, 62.8 to 305.5) microg x h/ml and median LPV trough concentration (C(trough)) of 10.8 (range, 4.1 to 25.3) microg/ml. In 16 subjects with SQV added, the SQV median AUC was 33.7 (range, 4.4 to 76.5) microg x h/ml and the median SQV C(trough) was 2.1 (range, 0.2 to 4.1) microg/ml. At week 24, 18 of 26 (69%) subjects remained in the study. Between weeks 24 and 48, one subject withdrew for nonadherence and nine withdrew for persistently high virus load. In antiretroviral-experienced children and adolescents with HIV, high doses of LPV/r with or without SQV offer safe options for salvage therapy, but the modest virologic response and the challenge of adherence to a regimen with a high pill burden may limit the usefulness of this approach.

Mutational patterns and correlated amino acid substitutions in the HIV-1 protease after virological failure to nelfinavir- and lopinavir/ritonavir-based treatments

Human immunodeficiency virus type 1 (HIV-1) antiviral drug resistance is a major consequence of therapy failure and compromises future therapeutic options. Nelfinavir and lopinavir/ritonavir-based therapies have been widely used in the treatment of HIV-infected patients, in combination with reverse transcriptase inhibitors. The aim of this observational study was the identification and characterization of mutations or combinations of mutations associated with resistance to nelfinavir and lopinavir/ritonavir in treated patients. Nucleotide sequences of 1,515 subtype B HIV-1 isolates from 1,313 persons with different treatment histories (including naïve and treated patients) were collected in 31 Spanish hospitals over the years 2002-2005. Chi-square contingency tests were performed to detect mutations associated with failure to protease inhibitor-based therapies, and correlated mutations were identified using statistical methods. Virological failure to nelfinavir was associated with two different mutational pathways. D30N and N88D appeared mostly in patients without previous exposure to protease inhibitors, while K20T was identified as a secondary resistance mutation in those patients. On the other hand, L90M together with L10I, I54V, A71V, G73S, and V82A were selected in protease inhibitor-experienced patients. A series of correlated mutations including L10I, M46I, I54V, A71V, G73S, and L90M appeared as a common cluster of amino acid substitutions, associated with failure to lopinavir/ritonavir-based treatments. Despite the relatively high genetic barrier of some protease inhibitors, a relatively small cluster of mutations, previously selected under drug pressure, can seriously compromise the efficiency of nelfinavir- and lopinavir/ritonavir-based therapies.