Literature DB >> 20885283

CD4 decline in seroconverter and seroprevalent individuals in the precombination of antiretroviral therapy era.

Sara Lodi1, Andrew Phillips, Giota Touloumi, Nikos Pantazis, Heiner C Bucher, Abdel Babiker, Geneviève Chêne, Philippe Vanhems, Kholoud Porter.   

Abstract

BACKGROUND: Studies based on seroconverters have increased our understanding of HIV disease. It is not clear, however, whether their disease progression differs from that of the general HIV population, given their reasons for presenting for testing.
METHODS: Using linear mixed models we compared CD4 decline rates for a seroconverter (CASCADE) and seroprevalent group (Concorde trial) with time origin being dates of seroconversion and randomization, respectively. Follow-up was censored at the earlier of last alive date and 1 January 1996. Analyses were adjusted for risk group, age and sex. To explore the role of symptomatic seroconversion we further categorized seroconverters into two groups: with and without an HIV test interval below 30 days as proxy.
RESULTS: The 7226 seroconverter and 1746 seroprevalent eligible individuals were mainly men (78 and 85%, respectively) infected through sex between men (52 and 63%) with mean [95% confidence interval (CI)] baseline CD4 cell count of 610 (602, 619) and 492 (479, 505) cells/μl, respectively. There was no evidence that rate of CD4 decline differs between the two groups even after adjusting for potential confounders (P = 0.67). Estimated loss in the year after reaching an arbitrary threshold of 400 cells/μl was 67 (95% CI 65, 69) and 67 (64, 69) cells/μl in the seroconverter and seroprevalent group, respectively. Whereas seroconverters with test interval below 30 days (n = 310) experienced faster decline, there was no difference in rates between other seroconverters and seroprevalent individuals (P = 0.87).
CONCLUSIONS: These data suggest that estimates of HIV progression derived from seroconverters are likely to hold more generally for the HIV-infected population.

Entities:  

Mesh:

Year:  2010        PMID: 20885283     DOI: 10.1097/QAD.0b013e32833ef6c4

Source DB:  PubMed          Journal:  AIDS        ISSN: 0269-9370            Impact factor:   4.177


  14 in total

1.  The undiagnosed HIV epidemic in France and its implications for HIV screening strategies.

Authors:  Virginie Supervie; Jacques D A Ndawinz; Sara Lodi; Dominique Costagliola
Journal:  AIDS       Date:  2014-07-31       Impact factor: 4.177

2.  Estimates of the Time From Seroconversion to Antiretroviral Therapy Initiation Among People Newly Diagnosed With Human Immunodeficiency Virus From 2006 to 2015, New York City.

Authors:  McKaylee M Robertson; Sarah L Braunstein; Donald R Hoover; Sheng Li; Denis Nash
Journal:  Clin Infect Dis       Date:  2020-11-05       Impact factor: 9.079

3.  Brief report: Time from infection with the human immunodeficiency virus to diagnosis, United States.

Authors:  H Irene Hall; Ruiguang Song; Célia Landmann Szwarcwald; Timothy Green
Journal:  J Acquir Immune Defic Syndr       Date:  2015-06-01       Impact factor: 3.731

4.  Characterizing sexual histories of women before formal sex-work in south India from a cross-sectional survey: implications for HIV/STI prevention.

Authors:  Sharmistha Mishra; Satyanarayana Ramanaik; James F Blanchard; Shiva Halli; Stephen Moses; T Raghavendra; Parinita Bhattacharjee; Rob Lorway; Marissa Becker
Journal:  BMC Public Health       Date:  2012-09-28       Impact factor: 3.295

5.  Differences in HIV natural history among African and non-African seroconverters in Europe and seroconverters in sub-Saharan Africa.

Authors:  Nikos Pantazis; Charles Morrison; Pauli N Amornkul; Charlotte Lewden; Robert A Salata; Albert Minga; Tsungai Chipato; Harold Jaffe; Shabir Lakhi; Etienne Karita; Kholoud Porter; Laurence Meyer; Giota Touloumi
Journal:  PLoS One       Date:  2012-03-06       Impact factor: 3.240

6.  Impact of exposure to intimate partner violence on CD4+ and CD8+ T cell decay in HIV infected women: longitudinal study.

Authors:  Rachel Jewkes; Kristin Dunkle; Nwabisa Jama-Shai; Glenda Gray
Journal:  PLoS One       Date:  2015-03-27       Impact factor: 3.240

7.  Modeling the impact of interventions along the HIV continuum of care in Newark, New Jersey.

Authors:  Ruthie B Birger; Timothy B Hallett; Anushua Sinha; Bryan T Grenfell; Sally L Hodder
Journal:  Clin Infect Dis       Date:  2013-10-17       Impact factor: 9.079

8.  Estimating HIV Incidence, Time to Diagnosis, and the Undiagnosed HIV Epidemic Using Routine Surveillance Data.

Authors:  Ard van Sighem; Fumiyo Nakagawa; Daniela De Angelis; Chantal Quinten; Daniela Bezemer; Eline Op de Coul; Matthias Egger; Frank de Wolf; Christophe Fraser; Andrew Phillips
Journal:  Epidemiology       Date:  2015-09       Impact factor: 4.822

9.  Role of HIV infection duration and CD4 cell level at initiation of combination anti-retroviral therapy on risk of failure.

Authors:  Sara Lodi; Andrew Phillips; Sarah Fidler; David Hawkins; Richard Gilson; Ken McLean; Martin Fisher; Frank Post; Anne M Johnson; Louise Walker-Nthenda; David Dunn; Kholoud Porter
Journal:  PLoS One       Date:  2013-09-24       Impact factor: 3.240

10.  Evaluation of rapid progressors in HIV infection as an extreme phenotype.

Authors:  Ashley D Olson; Marguerite Guiguet; Robert Zangerle; John Gill; Santiago Perez-Hoyos; Sara Lodi; Jade Ghosn; Maria Dorrucci; Anne Johnson; Mette Sannes; Santiago Moreno; Kholoud Porter
Journal:  J Acquir Immune Defic Syndr       Date:  2014-09-01       Impact factor: 3.731

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.