Fatigue in multiple sclerosis patients with different clinical phenotypes: a clinical and magnetic resonance imaging study.
PMS
RRMS
depression
disability
fatigue
Journal
European journal of neurology
ISSN: 1468-1331
Titre abrégé: Eur J Neurol
Pays: England
ID NLM: 9506311
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
06
07
2020
accepted:
06
08
2020
pubmed:
12
8
2020
medline:
24
6
2021
entrez:
12
8
2020
Statut:
ppublish
Résumé
The prevalence of fatigue and its relation with clinical, neuropsychological and brain magnetic resonance imaging (MRI) variables in a large cohort of multiple sclerosis (MS) patients was investigated. The Modified Fatigue Impact Scale and its subdomains were collected from 725 healthy controls and 366 MS patients [238 relapsing-remitting (RRMS) and 128 progressive (PMS)]. For the Modified Fatigue Impact Scale global and subdomains, MS patients were classified as fatigued (F-MS) or non-fatigued (NF-MS) according to cut-off values provided by logistic regression models with a specificity of 90% (i.e. a 10% false-positive rate in classifying healthy controls). MS patients underwent neurological, neuropsychological and MRI evaluations. Clinical and MRI measures were compared between F-MS and NF-MS patients using age-, sex- and phenotype-adjusted linear models. Heterogeneities between phenotypes were tested with specific interaction terms. Global fatigue affected 174 (47.5%) MS patients, being more prevalent in PMS (PMS 64.1% vs. RRMS 38.7%, P < 0.001). For all dichotomizations, F-MS were older (P from <0.001 to 0.012) and more depressed (P < 0.001) than NF-MS patients. Compared to NF-MS, cognitive F-MS patients had lower education (P = 0.035). Compared to NF-MS, patients with global and physical fatigue had higher Expanded Disability Status Scale only for RRMS (P < 0.001). Only RRMS patients with physical fatigue had lower brain (P = 0.05), white matter (P = 0.039) and thalamic volumes (P = 0.022) compared to NF-MS patients. In MS, fatigue is associated with older age, lower education and higher depression. Only in RRMS, fatigue is associated with Expanded Disability Status Scale and brain atrophy. A plateauing effect of disability and structural damage can explain the lack of associations in PMS.
Sections du résumé
BACKGROUND AND PURPOSE
The prevalence of fatigue and its relation with clinical, neuropsychological and brain magnetic resonance imaging (MRI) variables in a large cohort of multiple sclerosis (MS) patients was investigated.
METHOD
The Modified Fatigue Impact Scale and its subdomains were collected from 725 healthy controls and 366 MS patients [238 relapsing-remitting (RRMS) and 128 progressive (PMS)]. For the Modified Fatigue Impact Scale global and subdomains, MS patients were classified as fatigued (F-MS) or non-fatigued (NF-MS) according to cut-off values provided by logistic regression models with a specificity of 90% (i.e. a 10% false-positive rate in classifying healthy controls). MS patients underwent neurological, neuropsychological and MRI evaluations. Clinical and MRI measures were compared between F-MS and NF-MS patients using age-, sex- and phenotype-adjusted linear models. Heterogeneities between phenotypes were tested with specific interaction terms.
RESULTS
Global fatigue affected 174 (47.5%) MS patients, being more prevalent in PMS (PMS 64.1% vs. RRMS 38.7%, P < 0.001). For all dichotomizations, F-MS were older (P from <0.001 to 0.012) and more depressed (P < 0.001) than NF-MS patients. Compared to NF-MS, cognitive F-MS patients had lower education (P = 0.035). Compared to NF-MS, patients with global and physical fatigue had higher Expanded Disability Status Scale only for RRMS (P < 0.001). Only RRMS patients with physical fatigue had lower brain (P = 0.05), white matter (P = 0.039) and thalamic volumes (P = 0.022) compared to NF-MS patients.
CONCLUSIONS
In MS, fatigue is associated with older age, lower education and higher depression. Only in RRMS, fatigue is associated with Expanded Disability Status Scale and brain atrophy. A plateauing effect of disability and structural damage can explain the lack of associations in PMS.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2549-2560Informations de copyright
© 2020 European Academy of Neurology.
Références
Krupp LB, Alvarez LA, LaRocca NG, Scheinberg LC. Fatigue in multiple sclerosis. Arch Neurol 1988; 45: 435-437.
Barak Y, Achiron A. Cognitive fatigue in multiple sclerosis: findings from a two-wave screening project. J Neurol Sci 2006; 245: 73-76.
Fisk JD, Pontefract A, Ritvo PG, Archibald CJ, Murray TJ. The impact of fatigue on patients with multiple sclerosis. Can J Neurol Sci 1994; 21: 9-14.
Lobentanz IS, Asenbaum S, Vass K, et al. Factors influencing quality of life in multiple sclerosis patients: disability, depressive mood, fatigue and sleep quality. Acta Neurol Scand 2004; 110: 6-13.
Penner IK, Paul F. Fatigue as a symptom or comorbidity of neurological diseases. Nat Rev Neurol 2017; 13: 662-675.
Oervik MS, Sejbaek T, Penner IK, Roar M, Blaabjerg M. Validation of the fatigue scale for motor and cognitive functions in a Danish multiple sclerosis cohort. Mult Scler Relat Disord 2017; 17: 130-134.
Jason LA, Evans M, Brown M, Porter N. What is fatigue? Pathological and nonpathological fatigue. PM&R 2010; 2: 327-331.
Diamond BJ, Johnson SK, Kaufman M, Graves L. Relationships between information processing, depression, fatigue and cognition in multiple sclerosis. Arch Clin Neuropsychol 2008; 23: 189-199.
Bakshi R, Shaikh ZA, Miletich RS, et al. Fatigue in multiple sclerosis and its relationship to depression and neurologic disability. Mult Scler 2000; 6: 181-185.
Gobbi C, Rocca MA, Pagani E, et al. Forceps minor damage and co-occurrence of depression and fatigue in multiple sclerosis. Mult Scler 2014; 20: 1633-1640.
Papadopoulou A, Muller-Lenke N, Naegelin Y, et al. Contribution of cortical and white matter lesions to cognitive impairment in multiple sclerosis. Mult Scler 2013; 19: 1290-1296.
Hanken K, Eling P, Klein J, Klaene E, Hildebrandt H. Different cortical underpinnings for fatigue and depression in MS? Mult Scler Relat Disord 2016; 6: 81-86.
Gobbi C, Rocca MA, Riccitelli G, et al. Influence of the topography of brain damage on depression and fatigue in patients with multiple sclerosis. Mult Scler 2014; 20: 192-201.
Greeke EE, Chua AS, Healy BC, Rintell DJ, Chitnis T, Glanz BI. Depression and fatigue in patients with multiple sclerosis. J Neurol Sci 2017; 380: 236-241.
Penner IK, Raselli C, Stocklin M, Opwis K, Kappos L, Calabrese P. The Fatigue Scale for Motor and Cognitive Functions (FSMC): validation of a new instrument to assess multiple sclerosis-related fatigue. Mult Scler 2009; 15: 1509-1517.
Flachenecker P, Kumpfel T, Kallmann B, et al. Fatigue in multiple sclerosis: a comparison of different rating scales and correlation to clinical parameters. Mult Scler 2002; 8: 523-526.
Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol 1989; 46: 1121-1123.
Krupp LB, Coyle PK, Doscher C, et al. Fatigue therapy in multiple sclerosis: results of a double-blind, randomized, parallel trial of amantadine, pemoline, and placebo. Neurology 1995; 45: 1956-1961.
Fisk JD, Ritvo PG, Ross L, Haase DA, Marrie TJ, Schlech WF. Measuring the functional impact of fatigue: initial validation of the fatigue impact scale. Clin Infect Dis 1994; 18: S79-S83.
Zimmermann C, Hohlfeld R. 'Fatigue' in multiple sclerosis. Nervenarzt 1999; 70: 566-574.
Amtmann D, Bamer AM, Noonan V, Lang N, Kim J, Cook KF. Comparison of the psychometric properties of two fatigue scales in multiple sclerosis. Rehabil Psychol 2012; 57: 159-166.
Tedeschi G, Dinacci D, Lavorgna L, et al. Correlation between fatigue and brain atrophy and lesion load in multiple sclerosis patients independent of disability. J Neurol Sci 2007; 263: 15-19.
Filippi M, Rocca MA. Toward a definition of structural and functional MRI substrates of fatigue in multiple sclerosis. J Neurol Sci 2007; 263: 1-2.
Morgante F, Dattola V, Crupi D, et al. Is central fatigue in multiple sclerosis a disorder of movement preparation? J Neurol 2011; 258: 263-272.
Calabrese M, Rinaldi F, Grossi P, et al. Basal ganglia and frontal/parietal cortical atrophy is associated with fatigue in relapsing-remitting multiple sclerosis. Mult Scler 2010; 16: 1220-1228.
Yarraguntla K, Seraji-Bozorgzad N, Lichtman-Mikol S, et al. Multiple sclerosis fatigue: a longitudinal structural MRI and diffusion tensor imaging study. J Neuroimaging 2018; 28: 650-655.
Yaldizli O, Glassl S, Sturm D, et al. Fatigue and progression of corpus callosum atrophy in multiple sclerosis. J Neurol 2011; 258: 2199-2205.
Novo AM, Batista S, Alves C, et al. The neural basis of fatigue in multiple sclerosis: a multimodal MRI approach. Neurol Clin Pract 2018; 8: 492-500.
Bisecco A, Caiazzo G, d'Ambrosio A, et al. Fatigue in multiple sclerosis: the contribution of occult white matter damage. Mult Scler 2016; 22: 1676-1684.
Palotai M, Cavallari M, Koubiyr I, et al. Microstructural fronto-striatal and temporo-insular alterations are associated with fatigue in patients with multiple sclerosis independent of white matter lesion load and depression. Mult Scler 2019; 26: 1708-1718.
Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 2018; 17: 162-173.
Kos D, Kerckhofs E, Nagels G, D'Hooghe MB, Ilsbroukx S. Origin of fatigue in multiple sclerosis: review of the literature. Neurorehabil Neural Repair 2008; 22: 91-100.
Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an Expanded Disability Status Scale (EDSS). Neurology 1983; 33: 1444-1152.
Fischer JS, Rudick RA, Cutter GR, Reingold SC. The multiple sclerosis functional composite measure (MSFC): an integrated approach to MS clinical outcome assessment. National MS Society Clinical Outcomes Assessment Task Force. Mult Scler 1999; 5: 244-250.
Amato MP, Portaccio E, Goretti B, et al. The Rao's Brief Repeatable Battery and Stroop Test: normative values with age, education and gender corrections in an Italian population. Mult Scler 2006; 12: 787-793.
Montgomery SA, Asberg M. A new depression scale designed to be sensitive to change. Br J Psychiatry 1979; 134: 382-389.
Chard DT, Jackson JS, Miller DH, Wheeler-Kingshott CA. Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes. J Magn Reson Imaging 2010; 32: 223-228.
Smith SM, Zhang Y, Jenkinson M, et al. Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. NeuroImage 2002; 17: 479-489.
Patenaude B, Smith SM, Kennedy DN, Jenkinson M. A Bayesian model of shape and appearance for subcortical brain segmentation. NeuroImage 2011; 56: 907-922.
Boyle GJ. Does item homogeneity indicate internal consistency or item redundancy in psychometric scales? Personality Individ Differ 1991; 12: 291-294.
Hidalgo de la Cruz M, d'Ambrosio A, Valsasina P, et al. Abnormal functional connectivity of thalamic sub-regions contributes to fatigue in multiple sclerosis. Mult Scler 2018; 24: 1183-1195.
Branco M, Ruano L, Portaccio E, et al. Aging with multiple sclerosis: prevalence and profile of cognitive impairment. Neurol Sci 2019; 40: 1651-1657.
Vestergaard S, Nayfield SG, Patel KV, et al. Fatigue in a representative population of older persons and its association with functional impairment, functional limitation, and disability. J Gerontol A Biol Sci Med Sci 2009; 64: 76-82.
Zengarini E, Ruggiero C, Perez-Zepeda MU, et al. Fatigue: relevance and implications in the aging population. Exp Gerontol 2015; 70: 78-83.
Salter A, Fox RJ, Tyry T, Cutter G, Marrie RA. The association of fatigue and social participation in multiple sclerosis as assessed using two different instruments. Mult Scler Relat Disord 2019; 31: 165-172.
Alvarenga-Filho H, Papais-Alvarenga RM, Carvalho SR, Clemente HN, Vasconcelos CC, Dias RM. Does fatigue occur in MS patients without disability? Int J Neurosci 2015; 125: 107-115.
Rocca MA, Parisi L, Pagani E, et al. Regional but not global brain damage contributes to fatigue in multiple sclerosis. Radiology 2014; 273: 511-520.
Rocca MA, Meani A, Riccitelli GC, et al. Abnormal adaptation over time of motor network recruitment in multiple sclerosis patients with fatigue. Mult Scler 2016; 22: 1144-1153.
Oberoi S, Robinson PD, Cataudella D, et al. Physical activity reduces fatigue in patients with cancer and hematopoietic stem cell transplant recipients: a systematic review and meta-analysis of randomized trials. Crit Rev Oncol Hematol 2018; 122: 52-59.
Witlox L, Hiensch AE, Velthuis MJ, et al. Four-year effects of exercise on fatigue and physical activity in patients with cancer. BMC Med 2018; 16: 86.
Learmonth YC, Motl RW. Physical activity and exercise training in multiple sclerosis: a review and content analysis of qualitative research identifying perceived determinants and consequences. Disabil Rehabil 2016; 38: 1227-1242.
Halabchi F, Alizadeh Z, Sahraian MA, Abolhasani M. Exercise prescription for patients with multiple sclerosis; potential benefits and practical recommendations. BMC Neurol 2017; 17: 185.
Rock PL, Roiser JP, Riedel WJ, Blackwell AD. Cognitive impairment in depression: a systematic review and meta-analysis. Psychol Med 2014; 44: 2029-2040.
Martins Da Silva A, Cavaco S, Moreira I, et al. Cognitive reserve in multiple sclerosis: protective effects of education. Mult Scler 2015; 21: 1312-1321.
Frankenmolen NL, Fasotti L, Kessels RPC, Oosterman JM. The influence of cognitive reserve and age on the use of memory strategies. Exp Aging Res 2018; 44: 117-134.
Kluger BM, Krupp LB, Enoka RM. Fatigue and fatigability in neurologic illnesses: proposal for a unified taxonomy. Neurology 2013; 80: 409-416.
Finsterer J, Mahjoub SZ. Fatigue in healthy and diseased individuals. Am J Hosp Palliat Care 2014; 31: 562-575.
Aldughmi M, Bruce J, Siengsukon CF. Relationship between fatigability and perceived fatigue measured using the neurological fatigue index in people with multiple sclerosis. Int J MS Care 2017; 19: 232-239.
Berard JA, Smith AM, Walker LAS. A Longitudinal evaluation of cognitive fatigue on a task of sustained attention in early relapsing-remitting multiple sclerosis. Int J MS Care 2018; 20: 55-61.
Penner IK. Evaluation of cognition and fatigue in multiple sclerosis: daily practice and future directions. Acta Neurol Scand 2016; 134: 19-23.
Novo AM, Batista S, Tenente J, et al. Apathy in multiple sclerosis: gender matters. J Clin Neurosci 2016; 33: 100-104.
Bakshi R. Fatigue associated with multiple sclerosis: diagnosis, impact and management. Mult Scler 2003; 9: 219-227.
Hu M, Muhlert N, Robertson N, Winter M. Perceived fatigue and cognitive performance change in multiple sclerosis: uncovering predictors beyond baseline fatigue. Mult Scler Relat Disord 2019; 32: 46-53.
Riccitelli G, Rocca MA, Forn C, Colombo B, Comi G, Filippi M. Voxelwise assessment of the regional distribution of damage in the brains of patients with multiple sclerosis and fatigue. AJNR Am J Neuroradiol 2011; 32: 874-879.
Yaldizli O, Penner IK, Frontzek K, et al. The relationship between total and regional corpus callosum atrophy, cognitive impairment and fatigue in multiple sclerosis patients. Mult Scler 2014; 20: 356-364.
Yang Y, Raine A. Prefrontal structural and functional brain imaging findings in antisocial, violent, and psychopathic individuals: a meta-analysis. Psychiatry Res 2009; 174: 81-88.
Eshaghi A, Marinescu RV, Young AL, et al. Progression of regional grey matter atrophy in multiple sclerosis. Brain 2018; 141: 1665-1677.
de la Cruz MH, d'Ambrosio A, Valsasina P, et al. Abnormal functional connectivity of thalamic sub-regions contributes to fatigue in multiple sclerosis. Mult Scler J 2018; 24: 1183-1195.