Impact of Changes Over Time in the Stanford University Genotypic Resistance Interpretation Algorithm

Concordance of genotypic resistance interpretation algorithms in HIV-1 infected patients: An exploratory analysis in Greece

PURPOSE

Genotypic resistance-related mutations in HIV-1 disease are often difficult to interpret. Different algorithms have been developed to provide meaningful application into clinical context. We aimed to compare, for the first time in Greece, the results of genotypic resistance derived from three interpretation algorithms.

METHODS

The sequences of 120 HIV 1-infected patients were tested for genotypic resistance to 19 antiretroviral (ARV) drugs (n = 2280 sequences). The interpretation results of Rega, ANRS and ViroSeq algorithms were compared.

RESULTS

Complete concordance was found for 2/19 ARV drugs, namely lamivudine and emptricitabine. Concordance was high for nucleoside reverse transcriptase inhibitors (NRTIs) and low for protease inhibitors (PIs). In inter-algorithm pairs, agreement was high between Rega and ViroSeq (kappa = 0.701), especially by ARV class, namely NRTIs (k = 0.869) and NNRTIs (k = 0.562). The only exception was noted for rilpivirine, where agreement was higher between ANRS and Rega (k = 0.410) compared to other inter-algorithm pairs (k = 0.018-0.055). By contrast, for PIs all comparisons yielded concordance equivalent to chance (k = 0.000).

CONCLUSIONS

Our exploratory analysis provided evidence of significant inter-algorithm discordances, especially for PIs and NNRTIs highlighting the importance of matching the results of different algorithms to achieve optimized risk stratification. Ongoing research could assist clinical physicians in interpreting complex genotypic resistance patterns.