Comparison of HIV type 1 protease inhibitor susceptibility results in viral samples analyzed by phenotypic drug resistance assays and by six resistance algorithms: an analysis of a subpopulation of the CHORUS cohort

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.

A study of seven rule-based algorithms for the interpretation of HIV-1 genotypic resistance data in Thailand

Since the free therapy program was started by the Thai government, the number of patients infected by HIV-1 with access to antiretroviral drugs has increased. The selection of effective interpretation algorithms for antiretroviral drug resistance has become even more important for clinical management. In this retrospective study, the level of agreement was evaluated in 721 antiretroviral-therapy failing HIV-1 subjects. Regarding genetic diversity, about 89% was recognized as non-B variants (CRF01_AE). The level of complete concordant interpretation score in all seven algorithms was recognized in non-nucleoside reverse transcriptase inhibitors (NNRTIs) and protease inhibitors (PIs) (67%), but not in nucleoside reverse transcriptase inhibitors (NRTIs) (52%). Over 10% of the major discordance score with TRUGENE was revealed in didanosine (Agence Nationale de Recherches sur le SIDA[ANRS]; Detroit Medical Centre [DMC]), abacavir (ANRS; Centre Hospitalier de Luxembourg [CHL]), and also with delavirdine, indinavir and amprenavir (Grupo de Aconselhamento Virológico [GAV]). A good to excellent agreement range of kappa scores was detected for most antiretroviral drugs. However, poor agreement with the TRUGENE system (k<0.40) was seen in the ANRS system with didanosine, abacavir and lopinavir; GAV system in indinavir and amprenavir; and DMC system in ritonavir. These might be an option for resource limited countries when selecting the use of a low cost or free algorithm interpretation, which has excellent agreement as the U.S. Food and Drug Administration (FDA)-approved TRUGENE commercial system.

Comparison of algorithms that interpret genotypic HIV-1 drug resistance to determine the prevalence of transmitted drug resistance

OBJECTIVE

We compared eight genotypic interpretation methods to determine whether the method used would affect the rates of reported transmitted drug resistance.

DESIGN

Retrospective cohort study.

METHODS

For the International AIDS Society-USA method we classified a mutation as resistant if it was a 'major' resistance-associated mutation. For the Stanford algorithm, we classified a mutation as resistant if the score was at least 60 (Stanford 60), and alternatively, if the score was at least 30 (Stanford 30). For Agence Nationale de Recherches sur le SIDA and Rega, we interpreted resistance as either 'intermediate resistance' or 'resistance' (ANRS 1 and Rega 1), and 'resistance' only (ANRS 2 and Rega 2). We also used the calibrated population resistance algorithm. We then determined the rates of transmitted drug resistance within the Acute Infection Early Disease Research Program cohort (n = 1311) enrolled between March 1995 and August 2006 using each method; agreement was assessed using kappa coefficients.

RESULTS

Differences in estimated rates of transmitted drug resistance using International AIDS Society-USA, calibrated population resistance, Stanford 30, ANRS 1, Rega 1 and Rega 2 methods were mostly minor for resistance to protease and non-nucleoside reverse transcriptase inhibitors (1% range) and more pronounced for nucleoside reverse transcriptase inhibitors (5% range). For these methods kappa agreement was substantial or almost perfect across all drug classes. The Stanford 60 was most conservative.

CONCLUSIONS

The persistent high rates of transmitted drug resistance support the need for continued genotypic surveillance. The currently available interpretation algorithms can be used for this purpose.