Discrete Norms and Regression-Based Formulae for Interpreting the Minimal Assessment of Cognitive Function in Multiple Sclerosis: A Canadian Normative Study

Thursday, June 2, 2016
Exhibit Hall
David P Marino, M.S. , University of Toledo, Toledo, OH
Jason A Berard, M.A. , The Ottawa Hosptial Research Institute, Ottawa, ON, Canada
Denis Cousineau, Ph.D. , University of Ottawa, Ottawa, ON, Canada
Anthony Feinstein, PhD, MD , Psychiatry, University of Toronto, Toronto, ON, Canada
Sarah A Morrow, MD , Western University, London, ON, Canada
Lisa A.S. Walker, Ph.D. , The Ottawa Hosptial Research Institute, Ottawa, ON, Canada

Background: The Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS; Benedict et al., 2002) is a consensus-based collection of neuropsychological tests designed to evaluate cognitive dysfunction in individuals with multiple sclerosis. Because the MACFIMS is comprised of different tests, it is typically scored using each respective published test manual leaving the examiner to make test interpretations from norms derived from different populations. 

Objectives: The goal of this study was to co-norm the MACFIMS tests to allow for improved psychometric interpretation. 

Methods: This study aggregated MACFIMS data sets from across three Canadian cities (i.e., Ottawa, Toronto, London) yielding a total of 330 healthy control participants from four different studies evaluating cognition in individuals with MS. 

Results: From these data traditional age-based discrete norms were derived. In addition, regression-based formulae controlling for demographics (sex, age, education) were established for ease of use in a clinical setting. The various demographic variables varied in their contribution to each MACFIMS test in the regression models; predicting 0-18% of the variance. 

Conclusions: Provision of these regression-based formulae will allow for more accurate interpretation of MACFIMS scores by allowing clinicians to correct for all relevant demographic variables simultaneously, leading to improved clinical decision making for individuals with multiple sclerosis. The provision of both discrete and regression-based options will allow clinicians the freedom to choose the scoring method best suited to their practice.