Disentangling Fatigue Dimensions in Multiple Sclerosis: Differential Associations with Health-Related Quality of Life Outcomes in RRMS.

Background

Fatigue is a highly disabling symptom in multiple sclerosis and is strongly associated with reduced health-related quality of life (HRQoL). However, whether distinct fatigue dimensions show differential associations with specific HRQoL domains remains unclear. This study investigated the relationship between physical, cognitive, and psychosocial fatigue and SF-36 outcomes in people with relapsing-remitting multiple sclerosis (RRMS).

Methods

Forty-four people with RRMS were included in this cross-sectional study. Participants were classified as fatigued or non-fatigued according to the Modified Fatigue Impact Scale (MFIS) total score cut-off. Group differences in SF-36 domains were examined using ANCOVAs adjusted for age, sex, disease duration, and disability, with additional sensitivity analyses adjusting for depressive symptoms. Partial Spearman correlations assessed associations between MFIS subscales and SF-36 domains across the whole sample, controlling for demographic and clinical covariates.

Results

Eighteen participants were classified as fatigued and 26 as non-fatigued. Fatigued participants showed significantly lower scores across all SF-36 domains. After additional adjustment for depressive symptoms, differences remained significant for Physical Functioning, Role Physical, General Health, Vitality, Social Functioning, and Role Emotional. Physical fatigue was inversely associated with several HRQoL domains, including physical, social, vitality, general health, and mental health-related outcomes. Psychosocial fatigue was associated with poorer Physical Functioning, Role Physical, Bodily Pain, and Social Functioning. Cognitive fatigue was not significantly associated with any SF-36 domain.

Conclusions

Physical and psychosocial fatigue appear to be the main fatigue dimensions associated with HRQoL impairment in RRMS. Dimension-specific fatigue assessment may help identify more individualized targets for patient-centered management.