Assessing the effectiveness of antiretroviral adherence interventions: Using marginal structural models to replicate the findings of randomized controlled trials

Maya L. Petersen, Yue Wang, Mark J. Van Der Laan, David R. Bangsberg

Research output: Contribution to journalReview article

37 Scopus citations

Abstract

Randomized controlled trials of interventions to improve adherence to antiretroviral medications are not always feasible. Marginal structural models (MSM) are a statistical methodology that aims to replicate the findings of randomized controlled trials using observational data. Under the assumption of no unmeasured confounders, 3 MSM estimators are available to estimate the causal effect of an intervention. Two of these estimators, G-computation and inverse probability of treatment weighted (IPTW), can be implemented using standard software. G-computation relies on fitting a multivariable regression of adherence on the intervention and confounders. Thus, it is related to the standard multivariable regression approach to estimating causal effects. In contrast, IPTW relies on fitting a multivariable logistic regression of the intervention on confounders. This article reviews the implementation of these methods, the assumptions underlying them, and interpretation of results. Findings are illustrated with a theoretic data example in which MSM are used to estimate the effect of a behavioral intervention on adherence to antiretroviral therapy.

Original languageEnglish (US)
Pages (from-to)S96-S103
JournalJournal of Acquired Immune Deficiency Syndromes
Volume43
Issue numberSUPPL. 1
DOIs
StatePublished - Dec 1 2006
Externally publishedYes

Keywords

  • Causal inference
  • Counterfactual
  • G-computation
  • HIV
  • Inverse probability of treatment
  • Randomized controlled trial

ASJC Scopus subject areas

  • Infectious Diseases
  • Pharmacology (medical)

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