Volume 31, Issue 18
Research Article

The parametric g‐formula to estimate the effect of highly active antiretroviral therapy on incident AIDS or death

Daniel Westreich

Corresponding Author

E-mail address: daniel.westreich@duke.edu

Department of Obstetrics and Gynecology, School of Medicine and Duke Global Health Institute, Duke University, Durham, NC, USA

Daniel Westreich, Department of Obstetrics and Gynecology, School of Medicine and Duke Global Health Institute, Duke University, Durham, NC, USA.

E‐mail: daniel.westreich@duke.edu

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Stephen R. Cole

Department of Epidemiology, Gillings School of Global Public Health, Chapel Hill, NC, USA

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Jessica G. Young

Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA

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Frank Palella

Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

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Phyllis C. Tien

Department of Medicine, University of California, San Francisco, CA, USA

San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA

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Lawrence Kingsley

Department of Infectious Diseases and Microbiology, University of Pittsburgh, Pittsburgh, PA, USA

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Stephen J Gange

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

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Miguel A. Hernán

Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA

Harvard–MIT Division of Health Sciences and Technology, Boston, MA, USA

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First published: 11 April 2012
Citations: 58

Abstract

The parametric g‐formula can be used to contrast the distribution of potential outcomes under arbitrary treatment regimes. Like g‐estimation of structural nested models and inverse probability weighting of marginal structural models, the parametric g‐formula can appropriately adjust for measured time‐varying confounders that are affected by prior treatment. However, there have been few implementations of the parametric g‐formula to date. Here, we apply the parametric g‐formula to assess the impact of highly active antiretroviral therapy on time to acquired immune deficiency syndrome (AIDS) or death in two US‐based human immunodeficiency virus cohorts including 1498 participants. These participants contributed approximately 7300 person‐years of follow‐up (49% exposed to highly active antiretroviral therapy) during which 382 events occurred and 259 participants were censored because of dropout. Using the parametric g‐formula, we estimated that antiretroviral therapy substantially reduces the hazard of AIDS or death (hazard ratio = 0.55; 95% confidence limits [CL]: 0.42, 0.71). This estimate was similar to one previously reported using a marginal structural model, 0.54 (95% CL: 0.38, 0.78). The 6.5‐year difference in risk of AIDS or death was 13% (95% CL: 8%, 18%). Results were robust to assumptions about temporal ordering, and extent of history modeled, for time‐varying covariates. The parametric g‐formula is a viable alternative to inverse probability weighting of marginal structural models and g‐estimation of structural nested models for the analysis of complex longitudinal data. Copyright © 2012 John Wiley & Sons, Ltd.

Number of times cited according to CrossRef: 58

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