ArticleBMC neurology2024
Exploring humanistic burden of fatigue in adults with multiple sclerosis: an analysis of US National Health and Wellness Survey data.
Article in BMC neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Associations Between Neuromuscular Fatigue, Anxiety, and Peripheral Biomarkers of Neuronal Injury, Inflammation, and Mitochondrial Dysfunction in Treatment-Naïve Relapsing-Remitting Multiple Sclerosis.Brain and behavior · 2026Article
- Disentangling Fatigue Dimensions in Multiple Sclerosis: Differential Associations with Health-Related Quality of Life Outcomes in RRMS.Medical sciences (Basel, Switzerland) · 2026Article
- Real-World Perspectives on Switching Patients with Multiple Sclerosis from Anti-CD20 Therapy to Cladribine Tablets from USA-Based Advanced Practice Providers: A Podcast.Advances in therapy · 2025Article
- Linking Pathogenesis to Fall Risk in Multiple Sclerosis.Archives of internal medicine research · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis retrospective study examined the humanistic burden of fatigue in patients with relapsing-remitting multiple sclerosis (RRMS), compared with adults without MS, using data from the 2017 and 2019 US National Health and Wellness Survey.
methodsThe 5-item Modified Fatigue Impact Scale (MFIS-5) was used to assess level of fatigue (MFIS-5 score <15: low fatigue [LF]; MFIS-5 score ≥15: high fatigue [HF]) in patients with RRMS. Health-related quality of life (HRQoL) measures (Short Form 36-Item Health Survey version 2, Euroqol-5 Dimensions-5 Levels [EQ-5D-5L], Patient Health Questionnaire-9 [PHQ-9], Generalized Anxiety Disorder-7 [GAD-7], Perceived Deficits Questionnaire-5) and treatment-related characteristics were assessed.
resultsIn total, 498 respondents were identified as RRMS (n=375 RRMS+LF, n=123 RRMS+HF) and compared with 1,494 matched non-MS controls. RRMS+LF and RRMS+HF had significantly lower Short Form 6 Dimensions health utility, Mental and Physical Component Summary, and EQ-5D-5L scores and higher PHQ-9 and GAD-7 scores, compared with matched non-MS controls (all p<0.001); scores were worse for RRMS+HF than RRMS+LF across all measures (all p<0.001). A higher proportion of RRMS+HF reported moderate-to-severe depression and moderate-to-severe anxiety, compared with RRMS+LF and matched non-MS controls (both p<0.001). Fatigue was a significant predictor of poor HRQoL across all measures (all p<0.001).
conclusionsPatients with RRMS experienced lower HRQoL with higher levels of fatigue, highlighting an unmet need. Results may help to inform physician-patient communication and shared decision-making to address fatigue and its associated impact on patients' HRQoL.
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