A genotypic drug resistance interpretation algorithm that significantly predicts therapy response in HIV-1-infected patients

Objectives: The development of a genotypic drug resistance interpretation algorithm, and the evaluation of its power to predict therapy outcome. Design: A rule-based algorithm was established by an individual expert and was based on published and inhouse results, independently from the data of the patients used in this evaluation. The predictive value of the algorithm for virological outcomes was retrospectively evaluated using the baseline genotype observed in patients on highly active antiretroviral therapy, failing virologically and subsequently starting a salvage regimen. Methods: The independent association between the susceptibility score (calculated according to the algorithm) and the virological response at 3 months, was analysed using multivariable logistic regression and multiple linear regression models. Results: In two clinical centres 240 patients were studied. At 3 months 35% had a viral load of 10 RNA copies/ml; 95% Cl -0.11 to -0.43; P=0.001) after adjusting for history of prior viral load