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Introduction: When used in combination, antiretroviral drugs are highly effective for suppressing HIV replication. Nevertheless, treatment failure commonly occurs and is generally associated with viral drug resistance. The choice of an alternative regimen may be guided by a drug-resistance test. However, interpretation of resistance from genotypic data poses a major challenge., Methods: As an alternative to current interpretation systems, we have developed artificial neural network (ANN) models to predict virological response to combination therapy from HIV genotype and other clinical information., Results: ANN models trained with genotype, baseline viral load and time to follow-up viral load (1154 treatment change episodes from multiple clinics), produced predictions of virological response that were highly significantly correlated with actual responses (r2 = 0.53; P < 0.00001) using independent test data from clinics that contributed training data. Augmented models, trained with the additional variables of baseline CD4+ T-cell count and four treatment history variables, were more accurate, explaining 69% of the variance in virological response. Models trained with the full input dataset, but only those data involving highly active antiretroviral therapy (three or more full-dose antiretroviral drugs in combination), performed at an intermediate level, explaining 61% of the variance. The augmented models performed less well when tested with data from unfamiliar clinics that had not contributed data to the training dataset, explaining 46% of the variance in response., Conclusion: These data indicate that ANN models can be quite accurate predictors of virological response to HIV therapy even for patients from unfamiliar clinics. ANN models therefore warrant further development as a potential tool to aid treatment selection.

Objective: To assess the prevalence of modest (< 10-fold) decreases in baseline non-nucleoside reverse transcriptase inhibitor (NNRTI) susceptibility and their impact on virological response to NNRTI-containing triple therapy in drug-naive individuals., Methods: Baseline HIV resistance phenotype, genotype and response to therapy were examined retrospectively for all antiretroviral-naive individuals initiating therapy with two nucleoside analogues and an NNRTI in British Columbia, Canada, between 05/1997 and 08/1999 (n = 279), followed until July 31 2001. Time to viral suppression (first of at least two consecutive plasma viral loads < 400 copies HIV RNA copies/ml) and viral rebound (to > or = 400 copies/ml after first pVL < 400 copies HIV RNA copies/ml), were estimated by Kaplan-Meier methods. Multivariate analyses were performed using Cox proportional hazards regression., Results: Nevirapine was the most commonly prescribed NNRTI (96%). Four- to 10-fold decreased susceptibility to NNRTIs was observed in > 30% of untreated individuals at baseline, an observation strongly driven by decreased susceptibility to delavirdine (22.4%). A > 10-fold decrease in susceptibility to any NNRTI was observed only rarely (< 2%). There was no association between four- and 10-fold decreased baseline susceptibility to NNRTIs and virological outcome (P > 0.05). In multivariate analyses, the strongest predictors of poor virological response to NNRTI-based therapy were baseline plasma viral load and the proportion of time on therapy in the first year of follow-up. There was no relationship between the presence of previously reported mutations associated with decreased NNRTI susceptibility (at codons 135 and 283 in HIV reverse transcriptase) and virological response., Conclusions: These data suggest that the clinically significant level of resistance to NNRTIs, particularly nevirapine, in drug-naive individuals is likely greater than four- to 10-fold.

A variety of key mutations in HIV reverse transcriptase (RT) have been associated with nucleoside reverse transcriptase inhibitor (NRTI) exposure, which give rise to a diverse range of effects in terms of altered drug susceptibilities, viral replicative capacity and RT biochemistry. There are three basic mechanisms of resistance conferred by specific mutations in the coding region of RT. The first is drug discrimination, whereby a particular drug or drugs are either selectively excluded from uptake or from the RT-primer-template catalytic complex. Drug discrimination is, for the most part, relatively specific for individual drugs. Repositioning of the template-primer to prevent a catalytically competent complex in the presence of a bound drug molecule has also been observed in some instances, and forms a second mechanism. The third, and potentially most significant for long-term efficacy of the NRTIs, is pyrophosphorolysis, the primary mode of resistance to zidovudine. Mutations selected by this drug or stavudine serve to elevate the natural rate of the reverse reaction for RT. Pyrophosphorolysis uncouples the last nucleoside monophosphate added to the proviral transcript, and attaches it to either a free pyrophosphate (regenerating a deoxynucleoside triphosphate) or to a nucleoside di- or triphosphate (usually ATP). Uncoupling a chain-terminating NRTI residue therefore rescues reverse transcription and reduces drug susceptibility across the class, since the process is not specific for the selecting drug. Of all the nucleoside-associated mutations, the best known and most studied are the six associated with thymidine analogue exposure. These six mutations (M41L, D67N, K70R, L210W, T215Y/F, K219Q) enhance RT pyrophosphorolysis to confer high-level viral resistance to zidovudine, and clinically significant loss of response to stavudine and didanosine. They have also been found to confer reduced susceptibility to lamivudine and abacavir, particularly when present alongside other NRTI-induced changes. Other key mutations generally confer more limited resistance to specific agents, although the primary lamivudine- and abacavir-associated M184V substitution generates a broad spectrum of drug-dependent phenotypes, and uncommon mutational complexes conferring resistance across the entire class are well known. In addition to 'classical' multi-nucleoside-resistant genotypes, database-driven 'virtual phenotyping' for accumulations of NRTI-associated mutations around a core of thymidine analogue-induced changes predicts drug susceptibilities below wild-type across the entire NRTI class, even in the absence of key mutations associated with individual agents. When the natural range of drug susceptibilities for treatment-naive isolates is used as the basis for defining resistance, retrospective analysis of clinical isolates in the Virco database shows a significantly increased incidence of reduced susceptibility for the dideoxy NRTIs (didanosine, stavudine and zalcitabine) that was undetected in previous assays. These data imply a cumulative degradation of response to

Objective: To assess the relationship between viral susceptibility at baseline and virological response in human immunodeficiency virus (HIV)-infected patients treated with multi-drug salvage regimens after multiple previous treatment failures., Design: Retrospective analysis of 50 patients from the Frankfurt HIV cohort who had received treatment with a minimum of six drugs, and for whom a sample for baseline viral phenotyping was available., Methods: Viral drug susceptibility was measured retrospectively from stored samples using the Antivirogram, a recombinant virus assay based method. Virological response was defined as a viral load of < 400 copies/ml at week 24. For analysis of treatment response, drop-outs were dealt with in two ways, either as failures (DAF) or censored (DAC). Several logistical regression models were applied to identify predictors of response, including baseline virus load, number of new drugs and phenotypic sensitivity scores., Results: At baseline, drug resistance was extensive: 96% of patients had viruses resistant to at least one drug class and 32% had viruses resistant to all three drug classes. In the DAF analysis, 39 patients experienced virological failure. In the DAC analysis, eight were censored and 31 patients experienced virological failure. In multivariate models that adjust for baseline viral load, the number of new drugs and total phenotypic sensitivity scores, the baseline viral load and phenotypic sensitivity score remained significantly associated with virological outcome, whereas in those adjusted for baseline viral load, the number of new drugs, NRTI phenotypic sensitivity score and PI phenotypic sensitivity score, only the latter remained significantly associated with virological outcome. Both the DAF and DAC analyses produced similar results. In all models used, virological failure was shown to be significantly associated with baseline viral load and phenotypic sensitivity score., Conclusions: In this retrospective analysis based on a small number of patients, viral drug susceptibility at baseline was strongly associated with virological outcome at 24 weeks, independent of covariates such as baseline viral load and treatment history. Baseline viral load also maintained a significant, independent association with virological outcome in most models.