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Activity Number: 103
Type: Invited
Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
Sponsor: ENAR
Abstract #314579 View Presentation
Title: MS Disease Progression: A Multiple Imputation Approach for Handling Missing Data
Author(s): Katherine Riester* and Lei Xu and Jacob Elkins and Ilya Lipkovich and Stacy Rachelle Lindborg
Companies: Biogen Idec and Biogen Idec and Biogen Idec and Quintiles and Biogen Idec
Keywords: Missing data ; Multiple Imputation
Abstract:

Sustained disease progression is often a key primary or secondary endpoint in multiple sclerosis clinical trials. Disease progression is measured by an observed decline in a disability clinical scale which is then confirmed 12 weeks later. If a subject has decline that cannot be confirmed because the confirmatory assessment is missing the subject is typically censored in the analysis and defined as not progressing. In this instance key information is lost since the subject has already had an observed decline during the first non-missing visit. We present a multiple imputation method to impute confirmed disease progression status when incomplete information is available under the missing at random (MAR) assumption. Using this approach logistic regression was used to predict the probability of confirmation among subjects with an initial decline at the last available visit after adjusting for key covariates. Multiple imputed datasets were analyzed using the standard approach for time to event data and the results were combined using the methods of Rubin. A case study will be presented summarizing how the method was implemented and the impact on the interpretation of the results.


Authors who are presenting talks have a * after their name.

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