BACKGROUND: Although the kinetics of CD4(+) cell counts have been extensively studied in antiretroviral-naive HIV-infected patients, data on individuals who have failed combination antiretroviral therapy (cART) are lacking. METHODS: This analysis was based on the ICONA Foundation Study. Subjects with > or = 1 episode of viral suppression after starting first-line cART were included (n = 3537). Following a viral rebound, patients who achieved another episode of viral suppression could reenter the analysis. The percentage of patients with an increase in CD4(+) cell count >300 cells/mm(3) was estimated using Kaplan-Meier techniques; the rate of CD4(+) cell count increase per year was estimated using a multivariable, multilevel linear model with fixed effects of intercept and slope. Multivariable models were also fitted to include several covariates. RESULTS: The median time to reach a CD4(+) cell count increase >300 cells/mm(3) from baseline was significantly associated with the number of failed regimens: 34 months, 41 months, 51 months, and 45 months in subjects without evidence of previous virological failure, or 1, 2, or > or = 3 previous virologically failed regimens, respectively (P < .001, by log-rank test). The annual estimated increases in CD4(+) cell count were 36 cells/mm(3) (95% confidence interval [CI], 34-38 cells/mm(3)), 28 cells/mm(3) (95% CI, 11-21 cells/mm(3)), 31 cells/mm(3) (95% CI, 26-36 cells/mm(3)), and 26 cells/mm(3) (95% CI, 18-33 cells/mm(3)), respectively. Differences in the annual CD4(+) cell count increase were observed between specific antiretrovirals. CONCLUSIONS: Subjects with > or = 1 virological failure took a longer time to reach a CD4(+) cell count >300 cell/mm(3) and had a slower annual increase than those without virological failure. Efforts should be made to optimize first-line cART, because this represents the best chance of achieving an effective CD4(+) response.
BACKGROUND: Although the kinetics of CD4(+) cell counts have been extensively studied in antiretroviral-naive HIV-infectedpatients, data on individuals who have failed combination antiretroviral therapy (cART) are lacking. METHODS: This analysis was based on the ICONA Foundation Study. Subjects with > or = 1 episode of viral suppression after starting first-line cART were included (n = 3537). Following a viral rebound, patients who achieved another episode of viral suppression could reenter the analysis. The percentage of patients with an increase in CD4(+) cell count >300 cells/mm(3) was estimated using Kaplan-Meier techniques; the rate of CD4(+) cell count increase per year was estimated using a multivariable, multilevel linear model with fixed effects of intercept and slope. Multivariable models were also fitted to include several covariates. RESULTS: The median time to reach a CD4(+) cell count increase >300 cells/mm(3) from baseline was significantly associated with the number of failed regimens: 34 months, 41 months, 51 months, and 45 months in subjects without evidence of previous virological failure, or 1, 2, or > or = 3 previous virologically failed regimens, respectively (P < .001, by log-rank test). The annual estimated increases in CD4(+) cell count were 36 cells/mm(3) (95% confidence interval [CI], 34-38 cells/mm(3)), 28 cells/mm(3) (95% CI, 11-21 cells/mm(3)), 31 cells/mm(3) (95% CI, 26-36 cells/mm(3)), and 26 cells/mm(3) (95% CI, 18-33 cells/mm(3)), respectively. Differences in the annual CD4(+) cell count increase were observed between specific antiretrovirals. CONCLUSIONS: Subjects with > or = 1 virological failure took a longer time to reach a CD4(+) cell count >300 cell/mm(3) and had a slower annual increase than those without virological failure. Efforts should be made to optimize first-line cART, because this represents the best chance of achieving an effective CD4(+) response.
Authors: Mingce Zhang; Adrian Clausell; Tanya Robinson; Jiyi Yin; Eric Chen; Leanne Johnson; Greta Weiss; Steffanie Sabbaj; Robert M Lowe; Fred H Wagner; Paul A Goepfert; Olaf Kutsch; Randy Q Cron Journal: J Immunol Date: 2012-08-08 Impact factor: 5.422
Authors: Monica Gandhi; Niloufar Ameli; Peter Bacchetti; Kathryn Anastos; Stephen J Gange; Howard Minkoff; Mary Young; Joel Milam; Mardge H Cohen; Gerald B Sharp; Yong Huang; Ruth M Greenblatt Journal: Clin Infect Dis Date: 2011-05 Impact factor: 9.079
Authors: E A Abayomi; A Somers; R Grewal; G Sissolak; F Bassa; D Maartens; P Jacobs; C Stefan; L W Ayers Journal: Transfus Apher Sci Date: 2011-04 Impact factor: 1.764
Authors: Howard B Gale; Steven R Gitterman; Heather J Hoffman; Fred M Gordin; Debra A Benator; Ann M Labriola; Virginia L Kan Journal: Clin Infect Dis Date: 2013-01-11 Impact factor: 9.079
Authors: Reena Rajasuriar; Maelenn Gouillou; Tim Spelman; Tim Read; Jennifer Hoy; Matthew Law; Paul U Cameron; Kathy Petoumenos; Sharon R Lewin Journal: PLoS One Date: 2011-06-02 Impact factor: 3.240
Authors: Kit N Simpson; Pamela P Pei; Jörgen Möller; Robert W Baran; Birgitta Dietz; William Woodward; Kristen Migliaccio-Walle; J Jaime Caro Journal: Pharmacoeconomics Date: 2013-05 Impact factor: 4.558