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OBJECTIVE: To evaluate CD4 cell count-driven strategies for the initiation of highly active antiretroviral therapy (HAART) in terms of the reduction of the incidence of AIDS-defining events in resource-poor settings. METHODS: Data from the Amsterdam Cohort Study on HIV infection and AIDS were used to estimate the hazard of AIDS in untreated HIV-1 infection and after initiation of HAART, respectively, conditional on CD4 cell count. Different strategies for initiating therapy were compared by calculating the expected HAART administration rate and 1-year cumulative AIDS incidence in three different population settings, varying in the stage of HIV-1 infection at the time of presentation. RESULTS: Among 695 HIV-1-infected cohort participants, the 1-year AIDS incidence density (ID) ranged from 3.2 per 100 person-years for CD4 cell counts 600-700 cells/mm3, to 31.9 per 100 person-years for CD4 cell counts 100-200 cells/mm3 and 77.9 per 100 person-years for CD4 cell counts below 100 cells/mm3. Upon initiation of HAART, the ID in the lowest CD4 strata declined to 13.3 and 16.3 per 100 person-years, respectively. Extrapolated to developing countries, supply of HAART to patients presenting with HIV-1 infection below 200 CD4 cells/mm3 is expected to give an administration rate of 67%, while the AIDS incidence will drop from over 30% to almost 10%. CONCLUSIONS: Introduction of HAART in populations with advanced HIV-1 infection can accomplish a threefold reduction of the AIDS incidence when HAART is administered to patients with CD4 cell counts below 200 cells/mm3. In a hospital-based setting in resource-poor environments this ensures an efficient treatment allocation.

Type

Journal

Antiviral therapy

Publication Date

02/2003

Volume

8

Pages

43 - 50

Addresses

Department of Human Retrovirology, Academic Medical Center, University of Amsterdam, The Netherlands.

Keywords

Humans, HIV Infections, CD4 Lymphocyte Count, Immunosuppression, Antiretroviral Therapy, Highly Active, Incidence, Cohort Studies, Homosexuality, Male, Models, Biological, Time Factors, Developing Countries, Medically Underserved Area, Male