Predicting differential responses to structured treatment interruptions during HAART.
Highly 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.
Department of Microbiology and Immunology, Department of Biomedical Engineering, The University of Michigan Medical School, Ann Arbor, MI 48109-0620, USA.
Seema H
SH
Bajaria
Glenn
G
Webb
Denise E
DE
Kirschner
D023241:Antiretroviral Therapy, Highly Active / Q000379:methods*; D015496:CD4-Positive T-Lymphocytes / Q000276:immunology; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D018450:Disease Progression; D015658:HIV Infections / Q000188:drug therapy* / Q000276:immunology / Q000821:virology; D015497:HIV-1; D006801:Humans; D008954:Models, Biological; D019562:Viral Load