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The utility of regression-based norms in interpreting the minimal assessment of cognitive function in multiple sclerosis (MACFIMS)

Published online by Cambridge University Press:  02 October 2009

BRETT A. PARMENTER
Affiliation:
Department of Psychology, Western State Hospital, Tacoma, Washington
S. MARC TESTA
Affiliation:
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
DAVID J. SCHRETLEN
Affiliation:
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
BIANCA WEINSTOCK-GUTTMAN
Affiliation:
Department of Neurology, Jacobs Neurological Institute, State University of New York at Buffalo, School of Medicine and Biomedical Sciences, Buffalo, New York
RALPH H. B. BENEDICT*
Affiliation:
Department of Neurology, Jacobs Neurological Institute, State University of New York at Buffalo, School of Medicine and Biomedical Sciences, Buffalo, New York
*
*Correspondence and reprint requests to: Ralph H. B. Benedict, Ph.D., Department of Neurology, 100 High Street (D-6), Buffalo, New York 14203. E-mail: [email protected]

Abstract

The Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) is a consensus neuropsychological battery with established reliability and validity. One of the difficulties in implementing the MACFIMS in clinical settings is the reliance on manualized norms from disparate sources. In this study, we derived regression-based norms for the MACFIMS, using a unique data set to control for standard demographic variables (i.e., age, age2, sex, education). Multiple sclerosis (MS) patients (n = 395) and healthy volunteers (n = 100) did not differ in age, level of education, sex, or race. Multiple regression analyses were conducted on the performance of the healthy adults, and the resulting models were used to predict MS performance on the MACFIMS battery. This regression-based approach identified higher rates of impairment than manualized norms for many of the MACFIMS measures. These findings suggest that there are advantages to developing new norms from a single sample using the regression-based approach. We conclude that the regression-based norms presented here provide a valid alternative to identifying cognitive impairment as measured by the MACFIMS. (JINS, 2010, 16, 6–16.)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2009

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