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Design strategies for repeated MRI scanning in multiple sclerosis clinical trials

University of British Columbia

A rising trend in multiple sclerosis (MS) clinical trials is the inclusion of a cohort study in which patients undergo repeated magnetic resonance imaging (MRI) scanning, most commonly at monthly intervals. Outcome measures for these cohorts are based on newly active lesions which are detected on the brain stem, and which are now commonly believed to be highly associated with MS exacerbations. These cohorts have the benefit of allowing researchers to see a clear treatment effect in a relatively shorter amount of time than with the more common clinical outcomes. Employing two large data sets, we attempt to address two distinct research topics relating to designs for such trials. The first topic is related to a published algorithm that uses placebo data to repeatedly simulate trials for a given efficacy as a means of producing sample size calculations. We present a validation of this algorithm, and propose a theoretical alternative to the recommended simulation. The second topic involves the question of optimal designs for repeated MRI trials in MS where the analysis will be based on summary statistics for the individual patients. Typically, designs have included one baseline scan, followed by several scans while under treatment. We develop a model for such data and an approach to examine optimality to recommend improvements to the most common choices for both the method of analysis and the design, such as the use of an ANCOVA model for the response, and the inclusion of multiple baselines as opposed to abundant treatment period scans.

Thesis/Dissertation

application/pdf

2009-06-27

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http://hdl.handle.net/2429/9769

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University of British Columbia

UBCV

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