Predicting quality of life in multiple sclerosis: accounting for physical disability, fatigue, cognition, mood disorder, personality, and behavior change
Introduction
Health-related quality of life (HQOL), or the capacity to derive satisfaction from meaningful behavior despite disease [1], is a topic of increasing interest to clinicians caring for MS patients. Research has consistently shown that MS patients produce lower HQOL scores than healthy controls [2], [3].
In recent years, there has been an expansion of studies examining factors associated with HQOL in MS [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18]. Collectively, these studies have revealed correlations between a number of clinical variables and HQOL indicators. In either correlation or regression analyses, poor HQOL was predicted by progressive disease course [11], [12], [14], [17], physical disability [4], [5], [8], [10], [14], self-reported fatigue [4], [5], depression [4], [6], [12], and cognitive impairment [16], [19]. Some tentative conclusions regarding the relative importance of these predictors have been offered. HQOL is strongly predicted by physical disability when the physical dimension of HQOL (e.g., limitations caused by weakness, poor coordination, gait disturbance) is emphasized [2], [5], [12], [13]. Depression may account for more variance than other predictors including EDSS or disease duration [6], and self-reported fatigue is strongly correlated with the physical and social aspects of HQOL [4]. In a recent longitudinal study [7], changes in HQOL were associated with poorer physical functioning, but not cognitive function. However, the scope of the cognitive evaluation was limited, and the study did not control for depression.
Thus, the major weakness of this research has been that multiple predictors were not considered simultaneously. If one seeks to determine the core disease and clinical features that determine MS-patient HQOL, the study design should encompass all potential predictors. It was our goal to conduct such a study. Specifically, we collected HQOL measurements in a large sample of MS patients and also assessed seven clinical domains (disease characteristics, physical disability, fatigue, cognitive function, personality traits, mood disorder, and behavioral dysfunction). Our objective was to determine which domain is most closely related to HQOL. We predicted that when all clinical domains are accounted for, depression would most strongly predict self-report indices of HQOL. In contrast, we hypothesized that vocational status would be predicted by more objective measures of cognitive and physical capacity.
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Subjects
The participants were 120 MS patients [20] and 44 healthy volunteers. The patients were recruited consecutively from an MS clinic. Informed consent was obtained per institutional review board requirements. Exclusion criteria were (a) current/past medical or psychiatric disorder (including major depressive disorder and bipolar disorder [21]) other than MS that could affect cognitive function, (b) substance abuse, (c) neurological impairment that may interfere with psychometric testing, (d) MS
Results
Group (MS vs. normal) differences on demographic factors were not significant by ANOVA and chi-square test. As expected, MS patients reported lower quality of life on MSQOL-54P (mean±S.D.: MS=57.6±19.0, NC=85.2±12.4, p<0.001), MSQOL-54M (MS=64.8±21.0, NC=84.1±11.1, p<0.001), and MSQOL-54O (MS=66.5±18.1, NC=79.7±11.6, p<0.001). Disabled were 54 or 45% of patients and 0 controls. Group differences were found in all predictor domains save personality (Table 1). Within the MS group, there were no
Discussion
Previous research predicted HQOL with various clinical measures, but heretofore, no prior study accounted for variables spanning the gamut of potential clinical domains. In the present study, for the first time, we controlled for the influence of demographic variables and predicted both HQOL and vocational status using measures of disease course, physical disability, fatigue, cognitive function, depression, personality, and behavior disorder. This hierarchical approach accounted for
Acknowledgements
We thank Barbara G. Vickery, MD for providing the MSQOL-54.
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