BACKGROUND: Highly active antiretroviral therapy (HAART) is being scaled up in developing countries. We compared baseline characteristics and outcomes during the first year of HAART between HIV-1-infected patients in low-income and high-income settings. METHODS: 18 HAART programmes in Africa, Asia, and South America (low-income settings) and 12 HIV cohort studies from Europe and North America (high-income settings) provided data for 4810 and 22,217, respectively, treatment-naïve adult patients starting HAART. All patients from high-income settings and 2725 (57%) patients from low-income settings were actively followed-up and included in survival analyses. FINDINGS: Compared with high-income countries, patients starting HAART in low-income settings had lower CD4 cell counts (median 108 cells per muL vs 234 cells per muL), were more likely to be female (51%vs 25%), and more likely to start treatment with a non-nucleoside reverse transcriptase inhibitor (NNRTI) (70%vs 23%). At 6 months, the median number of CD4 cells gained (106 cells per muL vs 103 cells per muL) and the percentage of patients reaching HIV-1 RNA levels lower than 500 copies/mL (76%vs 77%) were similar. Mortality was higher in low-income settings (124 deaths during 2236 person-years of follow-up) than in high-income settings (414 deaths during 20,532 person-years). The adjusted hazard ratio (HR) of mortality comparing low-income with high-income settings fell from 4.3 (95% CI 1.6-11.8) during the first month to 1.5 (0.7-3.0) during months 7-12. The provision of treatment free of charge in low-income settings was associated with lower mortality (adjusted HR 0.23; 95% CI 0.08-0.61). INTERPRETATION: Patients starting HAART in resource-poor settings have increased mortality rates in the first months on therapy, compared with those in developed countries. Timely diagnosis and assessment of treatment eligibility, coupled with free provision of HAART, might reduce this excess mortality.
BACKGROUND: Highly active antiretroviral therapy (HAART) is being scaled up in developing countries. We compared baseline characteristics and outcomes during the first year of HAART between HIV-1-infected patients in low-income and high-income settings. METHODS: 18 HAART programmes in Africa, Asia, and South America (low-income settings) and 12 HIV cohort studies from Europe and North America (high-income settings) provided data for 4810 and 22,217, respectively, treatment-naïve adult patients starting HAART. All patients from high-income settings and 2725 (57%) patients from low-income settings were actively followed-up and included in survival analyses. FINDINGS: Compared with high-income countries, patients starting HAART in low-income settings had lower CD4 cell counts (median 108 cells per muL vs 234 cells per muL), were more likely to be female (51%vs 25%), and more likely to start treatment with a non-nucleoside reverse transcriptase inhibitor (NNRTI) (70%vs 23%). At 6 months, the median number of CD4 cells gained (106 cells per muL vs 103 cells per muL) and the percentage of patients reaching HIV-1 RNA levels lower than 500 copies/mL (76%vs 77%) were similar. Mortality was higher in low-income settings (124 deaths during 2236 person-years of follow-up) than in high-income settings (414 deaths during 20,532 person-years). The adjusted hazard ratio (HR) of mortality comparing low-income with high-income settings fell from 4.3 (95% CI 1.6-11.8) during the first month to 1.5 (0.7-3.0) during months 7-12. The provision of treatment free of charge in low-income settings was associated with lower mortality (adjusted HR 0.23; 95% CI 0.08-0.61). INTERPRETATION: Patients starting HAART in resource-poor settings have increased mortality rates in the first months on therapy, compared with those in developed countries. Timely diagnosis and assessment of treatment eligibility, coupled with free provision of HAART, might reduce this excess mortality.
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Authors: Viviane D Lima; Katherine J Lepik; Wendy Zhang; Katherine A Muldoon; Robert S Hogg; Julio S G Montaner Journal: Can J Public Health Date: 2010 Sep-Oct
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Authors: B Tonwe-Gold; D K Ekouevi; C A Bosse; S Toure; M Koné; R Becquet; V Leroy; P Toro; F Dabis; W M El Sadr; E J Abrams Journal: Trop Med Int Health Date: 2009-02 Impact factor: 2.622
Authors: Martin W G Brinkhof; Matthias Egger; Andrew Boulle; Margaret May; Mina Hosseinipour; Eduardo Sprinz; Paula Braitstein; François Dabis; Peter Reiss; David R Bangsberg; Martin Rickenbach; Jose M Miro; Landon Myer; Amanda Mocroft; Denis Nash; Olivia Keiser; Margaret Pascoe; Stefaan van der Borght; Mauro Schechter Journal: Clin Infect Dis Date: 2007-10-22 Impact factor: 9.079