PubMed · 16078811
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Carol M Dunckley. 2005. Julius.. https://doi.org/10.1002/chp.18
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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 consider the application of instrumental variable techniques in a longitudinal clinical trial in paediatric HIV/AIDS, with a substantial degree of non-compliance to randomized treatment (Nelfinavir versus placebo) and with left censoring of the outcome variable (HIV RNA concentration). We consider in detail the assumptions and implications behind the inclusion and exclusion of interactions between randomized arm and baseline covariates in modelling actual treatment received, and between treatment and baseline covariates in modelling outcome. Estimated treatment effects were sensitive to inclusion of interactions, and we show how such sensitivity can be explored and explained.
During the past decade and a half, quantitation of plasma-associated human immunodeficiency virus type 1 (HIV-1) RNA level, or HIV-1 load, has been validated in clinical practice and clinical trials as an important surrogate marker of HIV-1 disease progression and of the potency and durability of antiretroviral regimens. This review highlights some of the history, accomplishments, and impact of Tom Merigan's laboratory on the use of HIV-1 load as a marker, as well as on updating technologies for determining HIV-1 load, their performance, interpretation of the results, and their use in clinical practice.