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Predicting Differential Responses to Structured Treatment Interruptions During HAART

dc.contributor.authorBajaria, Seema H.
dc.contributor.authorWebb, Glenn F.
dc.contributor.authorKirschner, Denise E.
dc.date.accessioned2011-03-29T15:55:44Z
dc.date.accessioned2011-03-29T15:55:44Z
dc.date.available2011-03-29T15:55:44Zen_US
dc.date.issued2004
dc.identifier.citationBulletin of Mathematical Biology (2004) 66, 1093–1118 <http://hdl.handle.net/2027.42/83362>en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/83362
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/pubmed?term=15294419
dc.description.abstractHighly active antiretroviral therapy (HAART) has been used clinically in various administration schemes for several years. However, due to the development of drug resistance, evolution of viral strains, serious side effects, and poor patient compliance, the combination of drugs used in HAART fails to effectively contain virus long term in a high proportion of patients. Our group and others have suggested a change to the usual regimen of continuous HAART through structured treatment interruptions (STIs). STIs may provide similar clinical benefits as continuous treatment such as reduced viral loads and reestablishment of CD4+ T cells while allowing patients drug holidays. We explore the use of STIs using a previously published model that accurately represents CD4+ T-cell counts and viral loads during both untreated HIV-1 infection and HAART therapy. We simulate the effects of different STI regimens including weekly and monthly interruptions together with variations in treatment initiation time. We predict that differential responses to STIs as observed in conflicting clinical trial data are impacted by the duration of the interruption, stage of infection at initiation of treatment, strength of the immune system in suppressing virus, or pre-therapy CD4+ T-cell count or virus load. Our results indicate that dynamics occurring below the limit of detection (LOD) are influenced by these factors, and contribute to reemergence or suppression of virus during interruptions. Simulations predict that short-term viral suppression with varying interruption strategies does not guarantee long-term clinical benefit.en_US
dc.language.isoen_USen_US
dc.publisherElsevier Ltd.en_US
dc.titlePredicting Differential Responses to Structured Treatment Interruptions During HAARTen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMicrobiology and Immunology
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumMicrobiology and Immunology, Department ofen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.identifier.pmid15294419
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/83362/1/bajaria.bmb2004.pdf
dc.identifier.doi10.1016/j.bulm.2003.11.003
dc.identifier.sourceBulletin of Mathematical Biologyen_US
dc.owningcollnameMicrobiology and Immunology, Department of


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