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Marginal structural Cox models for estimating the association between ?-interferon exposure and disease progression in a multiple sclerosis cohort.


ABSTRACT: Longitudinal observational data are required to assess the association between exposure to ?-interferon medications and disease progression among relapsing-remitting multiple sclerosis (MS) patients in the "real-world" clinical practice setting. Marginal structural Cox models (MSCMs) can provide distinct advantages over traditional approaches by allowing adjustment for time-varying confounders such as MS relapses, as well as baseline characteristics, through the use of inverse probability weighting. We assessed the suitability of MSCMs to analyze data from a large cohort of 1,697 relapsing-remitting MS patients in British Columbia, Canada (1995-2008). In the context of this observational study, which spanned more than a decade and involved patients with a chronic yet fluctuating disease, the recently proposed "normalized stabilized" weights were found to be the most appropriate choice of weights. Using this model, no association between ?-interferon exposure and the hazard of disability progression was found (hazard ratio = 1.36, 95% confidence interval: 0.95, 1.94). For sensitivity analyses, truncated normalized unstabilized weights were used in additional MSCMs and to construct inverse probability weight-adjusted survival curves; the findings did not change. Additionally, qualitatively similar conclusions from approximation approaches to the weighted Cox model (i.e., MSCM) extend confidence in the findings.

SUBMITTER: Karim ME 

PROVIDER: S-EPMC4082342 | biostudies-other | 2014 Jul

REPOSITORIES: biostudies-other

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Marginal structural Cox models for estimating the association between β-interferon exposure and disease progression in a multiple sclerosis cohort.

Karim Mohammad Ehsanul ME   Gustafson Paul P   Petkau John J   Zhao Yinshan Y   Shirani Afsaneh A   Kingwell Elaine E   Evans Charity C   van der Kop Mia M   Oger Joel J   Tremlett Helen H  

American journal of epidemiology 20140617 2


Longitudinal observational data are required to assess the association between exposure to β-interferon medications and disease progression among relapsing-remitting multiple sclerosis (MS) patients in the "real-world" clinical practice setting. Marginal structural Cox models (MSCMs) can provide distinct advantages over traditional approaches by allowing adjustment for time-varying confounders such as MS relapses, as well as baseline characteristics, through the use of inverse probability weight  ...[more]

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