Fatigue at time of CIS is an independent predictor of a subsequent diagnosis of multiple sclerosis

Runia, Tessel F.; Jafari, Naghmeh; Siepman, Dorine A M; Hintzen, Rogier Q.

doi:10.1136/jnnp-2014-308374

Cited by 56 publications

(54 citation statements)

References 28 publications

(24 reference statements)

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“…It has also been reported that the contribution of fatigue to depression severity in patients with MS is higher than in idiopathic depressive disorder . Fatigue is not only associated with patient‐reported HRQoL in cross‐sectional and longitudinal analyses, but it is also a predictor of disease activity and progression in patients with CIS and MS .…”

Section: Discussionmentioning

confidence: 96%

Fatigue and depression predict quality of life in patients with early multiple sclerosis: a longitudinal study

Nourbakhsh

Julián

Waubant

2016

Euro J of Neurology

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Section: Discussionmentioning

confidence: 96%

Fatigue and depression predict quality of life in patients with early multiple sclerosis: a longitudinal study

Nourbakhsh

Julián

Waubant

2016

Euro J of Neurology

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“…Fatigue is a debilitating yet common symptom affecting about 66% to 75% of individuals with multiple sclerosis (MS). [1][2][3][4] It can present early on in the disease course; 5 indeed the presence of fatigue in those with clinically isolated syndromes is an independent risk factor for the development of clinically definite MS, 6 although the mechanisms by which fatigue arises are not completely understood. 7,8 In the neuromyelitis optica spectrum disorders (NMOSD) clinic, fatigue is also a frequent complaint.…”

Section: Introductionmentioning

confidence: 99%

Factors associated with fatigue in CNS inflammatory diseases with AQP4 and MOG antibodies

Yeo

Passos

Muhammed

et al. 2020

Ann Clin Transl Neurol

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Objective Fatigue is a common and disabling symptom amongst people with multiple sclerosis, however it has not been compared across the central nervous system (CNS) inflammatory diseases associated with aquaporin‐4 (AQP4) and myelin oligodendrocyte glycoprotein (MOG) antibodies (Ab). We explored the factors associated with fatigue within and across the two diseases, and compared fatigue levels between them. Methods We performed a cross‐sectional study of 90 AQP4‐Ab and 44 MOG‐Ab patients. Fatigue was assessed using the Modified Fatigue Impact Scale (MFIS). Clinical, demographic, and psychometric (anxiety, depression, pain) data were used as independent variables. Multivariable linear regression was used to identify significant independent variables associated with fatigue within and across the two diseases. Results Within AQP4‐Ab patients, age (P = 0.002), disease duration (P = 0.004), number of clinical attacks (P = 0.001), disability (P = 0.007), pain interference (P < 0.001), anxiety (P = 0.026), and depression (P < 0.001) were significant independent variables. Interestingly, disease duration had a negative association with fatigue (P = 0.004). Within MOG‐Ab patients, pain interference score (P < 0.001) and anxiety (P = 0.001) were significant independent variables. Although fatigue was worse in AQP4‐Ab patients compared to MOG‐Ab patients (P = 0.008) in all patients as well as in those who ever had transverse myelitis (P = 0.023), this was driven by the differences in age, disability and pain interference rather than antibody subtype itself. Interpretation Multiple factors, but not the antibody specificity, appear to contribute to fatigue in antibody positive CNS inflammatory diseases. A multifaceted treatment approach is needed to better manage the physical, cognitive, and psychosocial aspects of fatigue in these patients.

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“…The location of the hyperintense T2 lesions further increases the predictive value of MRI, with brainstem and spinal cord lesions heralding a relatively higher risk of further demyelinating activity [140,141] . Moreover, quantitative changes, presenting as accelerated global or regional brain atrophy contribute to the prediction of the Time from CIS Reference Follow-up (years) Conversion rate, % n Giorgio et al [188] Kuhle et al [59] Kuhle et al [59] Ruet et al [189] Ruet et al [189] Mitjana et al [190] Hartung et al [191] Comi et al [192] Tintore et al [141] Kalincik et al [119] Ferraro et al [144] Tintore et al [136] Tintore et al [136] Kinkel et al [193] Miller et al [194] Filippi et al [195] Runia et al [196] Sombekke et al [140] Chard et al [197] Chard et al [197] DiFilippo et al [142] Patrucco et al [198] Rovaris et al [199] Brex et al [200] Dalton et al [201] Dalton et al [202] Villar et al [203] Liu et al [204] Magraner et al [205] 1 second attack [119,137,142,143] . Laboratory analysis of cerebrospinal fluid is another commonly used paraclinical tool.…”

Section: Relapses and The Diagnosis Of Msmentioning

confidence: 99%

Multiple Sclerosis Relapses: Epidemiology, Outcomes and Management. A Systematic Review

Kalinčík

2015

Neuroepidemiology

134

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Relapses (episodic exacerbations of neurological signs or symptoms) are a defining feature of relapsing-remitting multiple sclerosis (MS), the most prevalent MS phenotype. While their diagnostic value relates predominantly to the definition of clinically definite MS, their prognostic value is determined by their relatively high associated risk of incomplete remission resulting in residual disability. The mechanisms governing a relapse incidence are unknown, but numerous modifiers of relapse risk have been described, including demographic and clinical characteristics, many of which represent opportunities for improved disease management. Also relapse phenotypes have been associated with patient and disease characteristics and an individual predisposition to certain phenotypic presentations may imply individual neuroanatomical disease patterns. While immunomodulatory therapies and corticosteroids represent the mainstay of relapse prevention and acute management, respectively, their effect has only been partial and further search for more efficient relapse therapies is warranted. Other areas of research include pathophysiology and determinants of relapse incidence, recurrence and phenotypes, including the characteristics of the relapsing and non-relapsing multiple sclerosis variants and their responsiveness to therapies.

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Fatigue at time of CIS is an independent predictor of a subsequent diagnosis of multiple sclerosis

Cited by 56 publications

References 28 publications

Fatigue and depression predict quality of life in patients with early multiple sclerosis: a longitudinal study

Fatigue and depression predict quality of life in patients with early multiple sclerosis: a longitudinal study

Factors associated with fatigue in CNS inflammatory diseases with AQP4 and MOG antibodies

Multiple Sclerosis Relapses: Epidemiology, Outcomes and Management. A Systematic Review

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