PubMed · 11905146
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Laurie Robert, Deirdre Rogers, Laureen Kunches. 2002. Postexposure prophylaxis.. https://pubmed.ncbi.nlm.nih.gov/11905146/
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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.
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The introduction of potent antiretroviral therapies for treatment of HIV infection typically results in a dramatic reduction in plasma HIV RNA concentration, often to levels undetectable by current measurement practices. However, although a high proportion of patients achieve 'undetectability', many then experience a return to a state of detectability at a later date. As evaluation of virologic response provides a useful measure of therapy efficacy, it is of interest to estimate the proportions of cases with undetectable viral load over time following commencement of treatment. These proportions depend on the rates of transition from detectability to undetectability and subsequent return to detectability, and may be related to covariates or risk factors, possibly differing in both transitions. We consider construction of detectability profiles as estimates of these proportions, based on parametric modelling of the component survival distributions. The method is applied to an examination of the effects of baseline CD4 T-cell lymphocyte counts on virologic response to therapy amongst patients of the Western Australian HIV Cohort Study.