title: Application of the Marginal Structural Model to Account for Suboptimal Adherence in a Randomized Controlled Trial.
abstract: BACKGROUND
  There is considerable interest in adjusting for suboptimal adherence in randomized controlled trials. A per-protocol analysis, for example removes individuals who fail to achieve a minimal level of adherence. One can also reassign non-adherers to the control group, censor them at the point of non-adherence, or cross them over to the control. However, there are biases inherent in each of these methods. Here, we describe an application of causal modeling to address this issue.
  
  
  METHODS
  The marginal structural model with inverse-probability weighting was implemented using a weighted generalized estimating equation model. Two ancillary models were developed to derive the weights. First, stepwise linear regression was used to model the observed percent weight loss, while stepwise logistic regression model was applied to model early discontinuation from the intervention. From these, participant- and time-specific weights were calculated.
  
  
  CONCLUSIONS
  This model is complicated and requires careful attention to detail. Which variables to force into the ancillary models, how to construct interaction terms, and how to address time-dependent covariates must be considered. Nevertheless, it can be used to great effect to predict intervention effects at full adherence. Moreover, by contrasting these results against intention-to-treat results, insights can be gained into the intrinsic physiologic effect of the intervention.
  
  
  BACKGROUND
  ClinicalTrials.gov Identifier NCT00427193.
authors.affiliation: Rho Federal Systems, 6330 Quadrangle Drive, Chapel Hill, NC 27517, USA.
authors.forename: James
authors.initials: J
authors.lastname: Rochon
authors.affiliation: Duke Clinical Research Institute, 2400 Pratt Street, Durham, NC 27710, USA.
authors.forename: Manjushri
authors.initials: M
authors.lastname: Bhapkar
authors.affiliation: Department of Biostatistics and Bioinformatics, Duke University Medical Center, 2424 Erwin Road, Durham, NC 27710, USA.
authors.forename: Carl F
authors.initials: CF
authors.lastname: Pieper
authors.affiliation: Duke Clinical Research Institute, 2400 Pratt Street, Durham, NC 27710, USA; Duke Molecular Physiology Institute, 300 North Duke Street, Durham, NC 27701, USA.
authors.forename: William E
authors.initials: WE
authors.lastname: Kraus
keywords: adherence; aging; calorie restriction; causal modeling; marginal structural model; weighted GEE model