Background: Clinically relevant cutoffs are needed for the interpretation of HIV-1 phenotypic resistance estimates as predicted by virtual phenotype HIV resistance analysis.
Methods: Using a clinical data set containing 2596 treatment change episodes in 2217 patients in 8 clinical trials and 2 population-based cohorts, drug-specific linear regression models were developed to describe the relation between baseline characteristics (resistance, viral load, and treatment history), new treatment regimen selected, and 8-week virologic outcome.
Results: These models were used to derive clinical cutoffs (CCOs) for 6 nucleoside/nucleotide reverse transcriptase inhibitors (zidovudine, lamivudine, stavudine, didanosine, abacavir, and tenofovir), 3 unboosted protease inhibitors (PIs; indinavir, amprenavir, and nelfinavir), and 4 ritonavir-boosted PIs (indinavir/ritonavir, amprenavir/ritonavir, saquinavir/ritonavir, lopinavir/ritonavir). The CCOs were defined as the phenotypic resistance levels (fold change [FC]) associated with a 20% and 80% loss of predicted wild-type drug effect and depended on the drug-specific dynamic range of the assay.
Conclusions: The proposed CCOs were better correlated with virologic response than were biological cutoffs and provide a relevant tool for estimating the resistance to antiretroviral drug combinations used in clinical practice. They can be applied to diverse patient populations and are based on a consistent methodologic approach to interpreting phenotypic drug resistance.