Marginal structural models for estimating the effect of highly active antiretroviral therapy initiation on CD4 cell count.
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.
Cole
Stephen R
SR
Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA. scole@jhsph.edu
Hernán
Miguel A
MA
Margolick
Joseph B
JB
Cohen
Mardge H
MH
Robins
James M
JM
D000163:Acquired Immunodeficiency Syndrome / Q000188:drug therapy*; D000328:Adult; D023241:Antiretroviral Therapy, Highly Active / Q000706:statistics & numerical data*; D015982:Bias; D018791:CD4 Lymphocyte Count / Q000706:statistics & numerical data*; D015984:Causality; D015986:Confounding Factors, Epidemiologic; D018450:Disease Progression; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical