PubMed · 12506871
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N Wongvipat. 1999. Adherence tips from down under.. https://pubmed.ncbi.nlm.nih.gov/12506871/
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BACKGROUND: HIV proviral sequencing overcomes the limit of plasma viral load requirement by detecting all the 'archived mutations', but the clinical relevance remains to be evaluated. METHODS: We included 25 participants with available proviral sequences (both intact and defective sequences available) and utilized the genotypic sensitivity score (GSS) to evaluate the level of resistance in their provirus and plasma virus. Defective sequences were further categorized as sequences with and without hypermutations. Personalized GSS score and total GSS score were calculated to evaluate the level of resistance to a whole panel of antiretroviral therapies and to certain antiretroviral therapy that a participant was using. The rate of sequences with drug resistance mutations (DRMs) within each sequence compartment (intact, defective and plasma viral sequences) was calculated for each participant. RESULTS: Defective proviral sequences harbored more DRMs than other sequence compartments, with a median DRM rate of 0.25 compared with intact sequences (0.0, P = 0.014) and plasma sequences (0.095, P = 0.30). Defective sequences with hypermutations were the major source of DRMs, with a median DRM rate of 1.0 compared with defective sequences without hypermutations (0.042, P < 0.001). Certain Apolipoprotein B Editing Complex 3-related DRMs including reverse transcriptase gene mutations M184I, E138K, M230I, G190E and protease gene mutations M46I, D30N were enriched in hypermutated sequences but not in intact sequences or plasma sequences. All the hypermutated sequences had premature stop codons due to Apolipoprotein B Editing Complex 3. CONCLUSION: Proviral sequencing may overestimate DRMs as a result of hypermutations. Removing hypermutated sequences is essential in the interpretation of proviral drug resistance testing.
We develop parametric maximum likelihood methods to adjust for treatment changes during follow-up in order to assess the causal effect of treatment in clinical trials with time-to-event outcomes. The accelerated failure time model of Robins and Tsiatis relates each observed event time to the underlying event time that would have been observed if the control treatment had been given throughout the trial. We introduce a bivariate parametric frailty model for time to treatment change and time to trial endpoint. Estimating equations which respect the randomization are constructed and compared to maximum likelihood methods in a simulation study. The Concorde trial of immediate versus deferred zidovudine in HIV infection is used as a motivating example and illustration of the methods.
GW4511, GW4751, and GW3011 showed IC50 values < or =2 nM against wild type HIV-1 and <10 nM against 16 mutants. They were particularly potent against NNRTI-resistant viruses containing Y181C-, K103N-, and K103N-based double mutations, which account for a significant proportion of the clinical failure of the three currently marketed NNRTIs. The antiviral data together with the favorable pharmacokinetic data of GW4511 suggested that these benzophenones possess attributes of a new NNRTI drug candidate.