@article {9307,
	title = {Comparison of statistical approaches for dealing with immortal time bias in drug effectiveness studies},
	journal = {American Journal of Epidemiology},
	volume = {184},
	year = {2016},
	pages = {325-335},
	abstract = {<p>In time-to-event analyses of observational studies of drug effectiveness, incorrect handling of the period between cohort entry and first treatment exposure during follow-up may result in immortal time bias. This bias can be eliminated by acknowledging a change in treatment exposure status with time-dependent analyses, such as fitting a time-dependent Cox model. The prescription time distribution matching (PTDM) method has been proposed as a simpler approach for controlling immortal time bias. Using simulation studies and theoretical quantification of bias, we compared the performance of the PTDM approach with that of the time-dependent Cox model in the presence of immortal time. Both assessments revealed that the PTDM approach did not adequately address immortal time bias. Based on our simulation results, another recently proposed observational data analysis technique, the sequential Cox approach, was found to be more useful than the PTDM approach (Cox: bias = -0.002, mean squared error = 0.025; PTDM: bias = -1.411, mean squared error = 2.011). We applied these approaches to investigate the association of β-interferon treatment with delaying disability progression in a multiple sclerosis cohort in British Columbia, Canada (Long-Term Benefits and Adverse Effects of Beta-Interferon for Multiple Sclerosis (BeAMS) Study, 1995{\textendash}2008).</p>
},
	keywords = {bias, confounding factors, epidemiologic methods, immortal time bias, Longitudinal Studies, Models, survival analysis},
	doi = {10.1093/aje/kwv445},
	author = {Karim, ME and Gustafson, P and Petkau, J and Tremlett, H and BeAMS Study Group}
}
@article { ISI:000339808700005,
	title = {Marginal structural Cox models for estimating the association between beta-interferon exposure and disease progression in a multiple sclerosis cohort},
	journal = {American Journal of Epidemiology},
	volume = {180},
	number = {2},
	year = {2014},
	pages = {160-171},
	publisher = {OXFORD UNIV PRESS INC},
	address = {JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA},
	abstract = {<p>Longitudinal observational data are required to assess the association between exposure to beta-interferon medications and disease progression among relapsing-remitting multiple sclerosis (MS) patients in the {\textquoteleft}{\textquoteleft}real-world{\textquoteright}{\textquoteright} 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 {\textquoteleft}{\textquoteleft}normalized stabilized{\textquoteright}{\textquoteright} weights were found to be the most appropriate choice of weights. Using this model, no association between beta-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.</p>
},
	keywords = {bias (epidemiology), causality, confounding factors (epidemiology), epidemiologic methods, inverse probability weighting, marginal structural Cox model, multiple sclerosis, survival analysis},
	doi = {10.1093/aje/kwu125},
	author = {Karim, ME and Gustafson, P and Petkau, J and Zhao, Y and Shirani, A and Kingwell, E and Evans, C and van der Kop, M and Oger, J and Tremlett, H}
}
