Rescaling the EDSS Using Rasch Analysis

Background: The EDSS is arguably one of the best and certainly the most commonly used measure of MS-related disability. However, there are scaling and psychometric limitations with the EDSS that have not been adequately addressed.

Objectives: Develop a method to rescale the EDSS that does not alter clinical practice.

Methods: Apply Item-Response Theory analytical techniques (Rasch analysis) to the functional system (FS) and ambulation scores to develop a revised scoring algorithm. Rasch analyses will be applied to data from the Gulf War Era MS cohort (GWEMSC) we recently assembled. Preliminary reliability and validity analyses will also be performed.

Results: There are 2,382 veterans available for analysis: 66% male; 69% white; 24% black; 6% Hispanic and 1% other; mean age at diagnosis was 33 ± 8 years; mean age at initial exam was 44 ± 9 years. The most commonly occurring FS was pyramidal (69%) followed by cerebellar (57%), sensory (52%), and brain stem (42%). The remaining FS occurred in 30% or less. Results from the Rasch analysis as well as the prelimianry reliability and validity analyses will be reported.

Conclusions: The aim of this study is to develop a revised scoring algorithm applied to the FS scores that will address many of the psychometric limitations of the EDSS. Rasch analysis assigns logit values to each of the scale items (FS) that can then be summed (and rescaled) to provide a true equal-interval scale that is nromally distributed. Thus, this method may provide reliable method to account for all MS-related symptoms in the scoring of the EDSS across the spectrum of disability.