Accuracy, precision, and consistency of expert HIV type 1 genotype interpretation: an international comparison (The GUESS Study).
BACKGROUND
Resistance testing is considered standard of care in HIV medicine, but there is no standard interpretation system for genotype tests. We sought to determine how much agreement exists within a group of experts in the interpretation of complex genotypes.


METHODS
Genotypes from clinical specimens were sent to an international panel of 12 resistance experts. Phenotypic susceptibility testing of these clinical isolates was performed with antivirogram. Experts predicted phenotype fold change category (<2.5-fold change, 2.5-4.0-fold change, >4.0- to 7.0-fold change, >7.0- to 10-fold change, >10- to 20-fold change, or >20-fold change) and predicted expected drug activity for each of 16 antiretroviral drugs. Experts were also asked to make treatment recommendations on the basis of the genotype.


RESULTS
The experts predicted the exact phenotype fold change category correctly 44% of the time, but they varied widely by antiretroviral drug (range, 25%-74%). The highest accuracy was observed for lamivudine (74%) and the nonnucleoside reverse transcriptase inhibitors (66%-69%). Experts generally predicted higher levels of resistance to the remaining nucleoside reverse transcriptase inhibitors than what was found by phenotypic testing. Agreement among experts in predicting phenotype fold change category ranged widely depending on the drug (median agreement, 42% [range, 28%-74%]); the same pattern was observed in predicting expected drug activity (median agreement, 45% [range, 32%-87%]). Experts agreed on treatment recommendations in a median of 79% of instances, and recommendations were consistent over time, with blinded retesting.


CONCLUSIONS
Although their ability to predict phenotype from a genotype varied for individual antiretroviral drugs, this expert panel had a high degree of agreement in deriving treatment recommendations from the genotype.
Zolopa
Andrew R
AR
Stanford University School of Medicine, Stanford, CA 94305-5107, USA. azolopa@stanford.edu
Lazzeroni
Laura C
LC
Rinehart
Alex
A
Vezinet
Françoise Brun
FB
Clavel
François
F
Collier
Ann
A
Conway
Brian
B
Gulick
Roy M
RM
Holodniy
Mark
M
Perno
Carlo-Frederico
CF
Shafer
Robert W
RW
Richman
Douglas D
DD
Wainberg
Mark A
MA
Kuritzkes
Daniel R
DR
D019380:Anti-HIV Agents / Q000494:pharmacology*; D003627:Data Interpretation, Statistical; D024882:Drug Resistance, Viral / Q000235:genetics; D005838:Genotype; D015658:HIV Infections / Q000821:virology; D016333:HIV Protease / Q000235:genetics; D017320:HIV Protease Inhibitors / Q000494:pharmacology; D054303:HIV Reverse Transcriptase / Q000235:genetics; D015497:HIV-1 / Q000187:drug effects* / Q000235:genetics*; D006801:Humans; D038622:Internationality; D008826:Microbial Sensitivity Tests / Q000379:methods / Q000592:standards; D009154:Mutation; D010641:Phenotype; D018894:Reverse Transcriptase Inhibitors / Q000494:pharmacology*
D019380:Anti-HIV Agents; D017320:HIV Protease Inhibitors; D018894:Reverse Transcriptase Inhibitors; D054303:HIV Reverse Transcriptase; D016333:HIV Protease