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Longitudinal correlates of fatigue in multiple sclerosis

Department of Neurology, State University of New York at Stony Brook, New York, USA

C Christodoulou

Department of Neurology, State University of New York at Stony Brook, New York, USA

LB Krupp

Department of Neurology, State University of New York at Stony Brook, New York, USA

on behalf of the New York State MS Consortium

Objective

To determine the predictors of longitudinal changes in fatigue based on pain, mood, and neurological impairment across multiple sclerosis (MS) subtypes.

Background

Fatigue is the most common symptom of MS but remains poorly understood. The New York State Multiple Sclerosis Consortium (NYSMSC) database offers a unique opportunity to longitudinally assess a variety of potential fatigue correlates in a very large and diverse MS sample.

Design/Methods

This study examined baseline and 1-year follow-up data on 2768 patients drawn from the NYSMSC database regarding fatigability, pain, depressive symptoms, MS subtype, and expanded disability status scale (EDSS). Correlates and predictors of fatigue were assessed in correlational and multiple regression analyses.

Results

Baseline fatigue, pain, and depression accounted for 34.6% of the variance in 1-year follow-up fatigue scores. Fatigue was lower in relapsing–remitting subjects than in other MS subtypes. Fatigue consistently correlated at baseline and follow-up with depressive symptoms, pain severity, and EDSS. Changes in fatigue correlated with changes in other variables.

Conclusions

Predictors of fatigue at 1 year include baseline fatigue, pain, mood, and EDSS. These symptoms are also correlated at baseline, follow-up, and in change scores. Identifying predictors of fatigue may facilitate patient management.

Key Words: fatigue • multiple sclerosis • pain • quality of life

Multiple Sclerosis, Vol. 15, No. 2, 258-261 (2009)
DOI: 10.1177/1352458508097466


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