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Application of the marginal structural model to account for suboptimal adherence in a randomized controlled trial

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 poi...

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Autores principales: Rochon, James, Bhapkar, Manjushri, Pieper, Carl F., Kraus, William E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5124349/
https://www.ncbi.nlm.nih.gov/pubmed/27900372
http://dx.doi.org/10.1016/j.conctc.2016.10.005
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author Rochon, James
Bhapkar, Manjushri
Pieper, Carl F.
Kraus, William E.
author_facet Rochon, James
Bhapkar, Manjushri
Pieper, Carl F.
Kraus, William E.
author_sort Rochon, James
collection PubMed
description 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. DISCUSSION: 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. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT00427193.
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spelling pubmed-51243492017-12-15 Application of the marginal structural model to account for suboptimal adherence in a randomized controlled trial Rochon, James Bhapkar, Manjushri Pieper, Carl F. Kraus, William E. Contemp Clin Trials Commun Article 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. DISCUSSION: 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. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT00427193. Elsevier 2016-11-03 /pmc/articles/PMC5124349/ /pubmed/27900372 http://dx.doi.org/10.1016/j.conctc.2016.10.005 Text en © 2016 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Rochon, James
Bhapkar, Manjushri
Pieper, Carl F.
Kraus, William E.
Application of the marginal structural model to account for suboptimal adherence in a randomized controlled trial
title Application of the marginal structural model to account for suboptimal adherence in a randomized controlled trial
title_full Application of the marginal structural model to account for suboptimal adherence in a randomized controlled trial
title_fullStr Application of the marginal structural model to account for suboptimal adherence in a randomized controlled trial
title_full_unstemmed Application of the marginal structural model to account for suboptimal adherence in a randomized controlled trial
title_short Application of the marginal structural model to account for suboptimal adherence in a randomized controlled trial
title_sort application of the marginal structural model to account for suboptimal adherence in a randomized controlled trial
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5124349/
https://www.ncbi.nlm.nih.gov/pubmed/27900372
http://dx.doi.org/10.1016/j.conctc.2016.10.005
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