“Time-to-event data with time-varying biomarkers measured only at study entry, with applications to Alzheimer’s disease”
NOTE: day and time
Abstract: Relating time-varying biomarkers of Alzheimer’s disease to time-to-event using a Cox model is complicated by the fact that Alzheimer’s disease biomarkers are sparsely collected, typically only at study entry; this is problematic since Cox regression with time-varying covariates requires observation of the covariate process at all failure times. The analysis might be simplified by using study entry as the time origin and treating the time-varying covariate measured at study entry as a fixed baseline covariate. I present conditions under which using an incorrect time origin of study entry results in consistent estimation of regression parameters when the time-varying covariate is continuous and fully observed. I also present conditions under which treating the time-varying covariate as fixed at study entry results in consistent estimation. I propose methods for estimating the regression parameter when a functional form can be assumed for the time-varying biomarker, which is measured only at study entry. I demonstrate the analytical results in a simulation study and apply the methods to data from the Rush Religious Orders Study and Memory and Aging Project and data from the Alzheimer’s Disease Neuroimaging Initiative.
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Division of Biostatistics seminars
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