Journal Article

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

Stephen R. Cole, Miguel A. Hernán, Joseph B. Margolick, Mardge H. Cohen and James M. Robins

in American Journal of Epidemiology

Published on behalf of Johns Hopkins Bloomberg School of Public Health

Volume 162, issue 5, pages 471-478
Published in print September 2005 | ISSN: 0002-9262
Published online September 2005 | e-ISSN: 1476-6256 | DOI:
Marginal Structural Models for Estimating the Effect of Highly Active Antiretroviral Therapy Initiation on CD4 Cell Count

Show Summary Details


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; AIDS, acquired immunodeficiency syndrome; CI, confidence interval; GEE, generalized estimating equations; HAART, highly active antiretroviral therapy; HIV, human immunodeficiency virus; IPTC, inverse probability-of-treatment-and-censoring; MSM, marginal structural model

Journal Article.  5547 words.  Illustrated.

Subjects: Public Health and Epidemiology

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.