Highlights
- •Fatigue is a disabling symptom commonly reported in relapsing-remitting multiple sclerosis (RRMS).
- •Previous evidence on the economic burden of fatigue in MS by fatigue status (low vs high) is limited.
- •This cross-sectional, retrospective, observational study of pooled data from the 2017 and 2019 US National Health and Wellness Survey evaluated the economic burden of fatigue.
- •Fatigue was positively and significantly associated with measures of economic burden.
- •RRMS poses a substantial economic burden on patients and society, particularly among those with high fatigue.
Abstract
Background
Fatigue, a common disabling symptom in multiple sclerosis (MS), is reported by the
majority of patients. However, evidence on the economic burden of fatigue in MS by
fatigue status is limited. This study aimed to evaluate the economic burden of fatigue,
including healthcare resource utilization (HCRU), labor force participation, and Work
Productivity and Activity Impairment (WPAI), among adults with relapsing-remitting
MS (RRMS) by low fatigue (LF) vs high fatigue (HF) and compared with adults without
MS.
Methods
This cross-sectional, retrospective, observational study included pooled data from
the 2017 and 2019 US National Health and Wellness Survey. The RRMS sample included
respondents aged ≥18 years who reported being diagnosed with MS by a healthcare provider
(HCP) and reported having RRMS. Non-MS controls included respondents aged ≥18 years
who did not report being diagnosed with MS by an HCP. Fatigue was measured using the
Modified Fatigue Impact Scale-5 (MFIS-5). Outcomes included HCRU (HCP visits, emergency
department visits, and hospitalizations in the past 12 months), labor force participation
(yes vs no), WPAI (absenteeism, presenteeism, total work productivity impairment,
and activity impairment), and annualized costs (direct medical, indirect, and total).
Respondents with RRMS were propensity-score matched to non-MS controls (ratio 1:3).
RRMS respondents were categorized as having LF (MFIS-5<15; RRMS+LF) and HF (MFIS-5≥15;
RRMS+HF). Bivariate analysis compared matched non-MS controls, RRMS+LF, and RRMS+HF.
Multivariable analyses were conducted among RRMS to evaluate associations between
fatigue (continuous variable) and outcomes.
Results
Overall, 498 respondents with RRMS (RRMS+LF, n=375; RRMS+HF, n=123) and 1494 matched non-MS controls were included. RRMS+HF and RRMS+LF had more
HCRU in the past 12 months than non-MS controls, whereas RRMS+HF had greater HCRU
than RRMS+LF (all p<0.05). WPAI was also higher among RRMS+HF and RRMS+LF, compared with non-MS controls,
as well as higher in RRMS+HF vs RRMS+LF (all p<0.001). RRMS+HF had significantly higher annualized direct medical costs than RRMS+LF
and matched non-MS controls ($19,978 vs $10,656, p=0.007; vs $8,048, p<0.001). Among employed respondents, RRMS+HF and RRMS+LF had higher annualized indirect
costs than non-MS controls, with RRMS+HF also having higher annualized indirect costs
than RRMS+LF ($23,647 vs $13,738 vs $8,001; all p<0.01); total annualized costs were higher in RRMS+HF and RRMS+LF, compared with non-MS
controls, as well as RRMS+HF vs RRMS+LF (all p<0.01). In multivariable models, fatigue was significantly and positively associated
with the number of HCP visits in the past 12 months (p=0.002); not participating in the labor force (p<0.001); and absenteeism, presenteeism, total work productivity impairment, and activity
impairment (all p<0.001).
Conclusion
RRMS poses a substantial economic burden on patients and society, and this burden
is disproportionately associated with HF.
Keywords
Abbreviations:
CCI (Charlson Comorbidity Index), CHAMPUS (Civilian Health and Medical Program of the Uniformed Services), CI (confidence interval), ED (emergency department), GLM (generalized linear model), HCP (healthcare provider), HCRU (healthcare resource utilization), HF (high fatigue), LCL (lower confidence limit), LF (low fatigue), MFIS-5 (Modified Fatigue Impact Scale-5), MS (multiple sclerosis), NA (not applicable), NHWS (National Health and Wellness Survey), RRMS (relapsing-remitting multiple sclerosis), SD (standard deviation), SE (standard error), UCL (upper confidence limit), US (United States), VA (Veterans Affairs), WPAI (Work Productivity and Activity Impairment)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: June 14, 2022
Accepted:
June 13,
2022
Received in revised form:
June 9,
2022
Received:
February 2,
2022
Identification
Copyright
© 2022 Published by Elsevier B.V.
