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American Journal of Epidemiology Advance Access published online on August 2, 2005
American Journal of Epidemiology, doi:10.1093/aje/kwi216
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American Journal of Epidemiology Copyright © 2005 by the Johns Hopkins Bloomberg School of Public Health All rights reserved
Received September 2, 2003
Accepted May 4, 2005

Article

Marginal Structural Models for Estimating the Effect of Highly Active Antiretroviral Therapy Initiation on CD4 Cell Count

Stephen R. Cole 1*, Miguel A. Hernán 2, Joseph B. Margolick 3, Mardge H. Cohen 4, and James M. Robins 5

1 Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
2 Department of Epidemiology, School of Public Health, Harvard University, Boston, MA
3 Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
4 Cook County Hospital, Chicago, IL
5 Department of Epidemiology, School of Public Health, Harvard University, Boston, MA; Department of Biostatistics, School of Public Health, Harvard University, Boston, MA

* To whom correspondence should be addressed.
Stephen R. Cole, E-mail: scole{at}jhsph.edu


  Abstract

The effect of highly active antiretroviral therapy (HAART) on the evolution of CD4-positive T-lymphocyte (CD4 cell) count among human immunodeficiency virus (HIV)-positive participants was estimated using inverse probability-of-treatment-and-censoring (IPTC)-weighted estimation of a marginal structural model. Of 1,763 eligible participants from two US cohort studies followed between 1996 and 2002, 60 percent initiated HAART. The IPTC-weighted estimate of the difference in mean CD4 cell count at 1 year among participants continuously treated versus those never treated was 71 cells/mm3 (95% confidence interval: 47.5, 94.6), which agrees with the reported results of randomized experiments. The corresponding estimate from a standard generalized estimating equations regression model that included baseline and most recent CD4 cell count and HIV type 1 RNA viral load as regressors was 26 cells/mm3 (95% confidence interval: 17.7, 34.3). These results indicate that nonrandomized studies of HIV treatment need to be analyzed with methods (e.g., IPTC-weighted estimation) that, in contrast to standard methods, appropriately adjust for time-varying covariates that are simultaneously confounders and intermediate variables. The 1-year estimate of 71 cells/mm3 was followed by an estimated continued increase of 29 cells/mm3 per year (estimated effect at 6 years: 216 cells/mm3), providing evidence that the large short-term effect found in randomized experiments persists and continues to improve over 6 years.

Keywords: acquired immunodeficiency syndrome; antiretroviral therapy, highly active; bias (epidemiology); causality; CD4 lymphocyte count; confounding factors (epidemiology); HIV.
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