Improving the Diagnosis of Neuromyelitis Optica Spectrum Disorder


Neuromyelitis optica (NMO) is an uncommon inflammatory autoimmune disease of the central nervous system that has a clinical and radiologic presentation similar to multiple sclerosis (MS).1-3 Unlike MS, however, NMO is mediated by an antibody response to aquaporin-4 (AQP4), a water channel located in brain regions in contact with cerebrospinal fluid (with specific localization to astrocytes at the blood-brain barrier). In addition to wide expression in the brain, spinal cord, and optic nerve, AQP4 is present in other organ systems throughout the body including the kidneys, stomach, skeletal muscle, lungs, tear and salivary glands, inner ear, olfactory epithelia, and placenta.1,2,4
 
The lack of firm criteria for the diagnosis of NMO led to expansion of the definition in 2015 to encompass a spectrum of disorders (NMOSD), including central clinical signs of optic neuritis, area postrema syndrome, acute myelitis, acute brainstem and diencephalic syndromes, and cerebral syndrome with typical brain lesions.2,4 

Clinical Manifestations and Disease Course

Attacks of NMOSD tend to be severe and escalate quickly, peaking within a week of onset.1 Common presenting symptoms include severe optic neuritis and bouts of severe intractable vomiting and hiccupping, along with clinical findings of extensive spinal cord inflammation.1

The usual course of NMOSD is not considered progressive; however, disability mounts with each successive attack.1 Epidemiologic evidence shows that without treatment, about half of those with NMOSD will either become wheelchair-bound or blind and up to one-third will die within 5 years of the first episode.1 Relapses must be treated aggressively over the long term with immunosuppressive therapies to prevent severe disability.1

Epidemiology

NMOSD is a rare disease that occurs worldwide, but similar to MS, it disproportionately affects women, with 5 to 10 times as many women than men having NMOSD.2 Onset has been reported between the ages of 3 years and 80 years, and at an average age of 40 years.2,4

Reviews of studies conducted globally have identified patterns that suggest higher incidence and prevalence of NMOSD among Black and Asian populations compared with White populations.5 Specifically, higher rates of NMOSD cluster closer to the equator, and people of African ethnicity appear to be at highest risk.5,6 It is difficult to draw firm conclusions in this regard because all of the evaluated studies were conducted in isolated populations, no direct comparisons were made between the study groups, and there were differences in the design of the various investigations.

Core Clinical Manifestations

Several constellations of symptoms or multisymptomatic syndromes seen in NMOSD can be mimicked by other disorders but may be used to distinguish NMOSD from MS. These are readily identified as 6 distinct syndromes.

Longitudinally extensive transverse myelitis (LETM): Patterns of inflammation of the central gray matter covering 3 or more contiguous vertebrae characterize this syndrome.1,7 Depending on the spinal cord region involved, LETM can produce paraplegia, tetraplegia, loss of bladder and sphincter control, pruritus and intense itching sensations, neuropathic pain, and paroxysmal tonic spasms.1,2 Short spinal cord lesions (<3 vertebral segments) may also be evident on magnetic resonance imaging (MRI) in up to 14% of cases.8 Although this finding mimics MS, the absence of brain lesions typical of MS provides strong evidence favoring the diagnosis of NMOSD.1

Optic neuritis: A primary symptom of both MS and NMOSD, optic neuritis causes vision loss and pain with eye movements.2 Specific patterns of optic neuritis may help clinicians to distinguish among the 2 diseases. In patients with NMOSD, for example, optic neuritis is often longitudinally extensive, affecting more than half of the optic nerve.7 In MS, optic neuritis is unilateral and anterior. A diagnosis of NMOSD is suggested by severe or bilateral optic neuritis with poor recovery.8 Optical coherence tomography studies have demonstrated that patients with NMO have a thinner retinal nerve fiber layer, suggesting a greater degree of axonal damage than that seen in MS.9,10

Area postrema syndrome (APS): Symptoms of intractable nausea, vomiting, and hiccups in APS are the presenting signs in approximately 12% of cases of NMOSD. Although these symptoms may suggest gastroenteritis, they are actually caused by activation of the emetic reflex due to inflammation of the area postrema in the medulla oblongata.1,11

Symptomatic brainstem syndrome: Brainstem lesions — which may be evident on MRI — are associated with a wide range of symptoms including hemiparesis, dysphagia, respiratory difficulties, oculomotor abnormalities, hearing loss, vertigo, and vestibular ataxia, as well as facial palsy, cranial nerve abnormalities, trigeminal neuralgia, and excessive yawning.1,2

Diencephalic syndrome: This syndrome, which suggests a hypothalamic pathology, is also a sign of NMOSD. Primary signs include narcolepsy or hypersomnia but may also include disturbances of temperature regulation and the endocrine system, obesity, anorexia, and hormonal overproduction (eg, hyperprolactinemia, dysmenorrhea). Thalamic lesions may cause severe anhidrosis or altered consciousness.2,12

Cerebral syndrome:Approximately 60% of patients with NMOSD may have brain involvement, which may be asymptomatic or cause seizures, encephalopathy, and hemiparesis.1

Cognitive Impairment

Demyelinating diseases may result in cognitive impairment. Several studies have reported the frequency of specific signs of cognitive impairment in patients with NMOSD, indicating that at least one-third will experience some type of cognitive deficit.2 The 2 highest reported rates of deficits in recent studies were 57% and 67%, but some studies reported rates ranging between 29% and 36%.2,13,14 Impairment was reported in the domains of attention, memory, processing speed, verbal fluency, verbal learning, and executive function.2 It is not clear what variables may influence the risk of cognitive impairment in individuals with NMOSD.13 Associations between advancing age and the duration of NMOSD have been suggested, but no studies to date have found a connection between degree of disability and diminished cognitive function.2

Making the Diagnosis

Despite its identification as a separate entity by Eugene Devic and Fernand Gault in 1894, NMO, also known as Devic disease, was widely regarded as a subtype of MS.2-4 The discovery in 2004 of serum antibodies to AQP4 was the first clear characteristic to differentiate NMOSD from clinical MS.2,3
 
As originally described, a diagnosis of NMO was based on the presence of bilateral optic neuritis and myelitis occurring simultaneously, with NMO generally considered a variant of MS. By the mid-20th century, relapses were often noted, and the advent of MRI technology revealed that patients had normal brain scans with 3 or more extensive transverse myelitis lesions occurring across multiple vertebral segments.3
 
The discovery of the AQP4 connection to NMO created the opportunity for an expanded definition of the disorder.4 The new criteria for NMOSD were updated in 2015; a person who tests AQP4 seropositive and has any of the 6 described core clinical syndromes is considered to be diagnosed with NMOSD.1,3

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What are the 6 core clinical manifestations of NMOSD?
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Longitudinally extensive transverse myelitis, optic neuritis, area postrema syndrome, symptomatic brainstem syndrome, diencephalic syndrome, and cerebral syndrome

Laboratory Distinctions 

AQP4  Expression
 
Comorbidities are common and related to AQP4 status; an estimated 1 in 4 patients with NMOSD who test positive for AQP4 antibodies have concomitant autoimmune disorders such as myasthenia gravis, systemic lupus erythematosus (SLE), Sjögren syndrome, or celiac disease.1 Although AQP4 antibodies are highly specific for NMO, not all patients testing positive for AQP4 antibodies meet all of the criteria for NMO. Conversely, some studies have identified AQP4 positivity associated with other autoimmune disorders, such as Sjögren syndrome and SLE.3
 
MOG Antibody Disease
 
Serum autoantibodies specific to myelin oligodendrocyte glycoprotein (MOG) found on myelin sheath surfaces present a new potential marker in support of a diagnosis of AQP4-seronegative NMOSD.2 The antibodies have been identified in the serum of 25% to 42% of AQP4-seronegative patients, suggesting an alternate pathophysiology that might lead to NMOSD.15,16

MRI Evidence

Early evidence suggested that brain lesions were atypical for NMO and more likely pointed to a diagnosis of MS.3 This was contradicted by data from Jarius and others in the early 2000s, who demonstrated the presence of brain lesions in approximately 60% of patients with NMO, which may in some cases meet the MRI diagnostic criteria for MS.3,17
 
MRI is an invaluable tool for distinguishing NMOSD lesions from those of MS and other demyelinating diseases.7 Although imaging results may be unremarkable in many patients with NMOSD, selected patients have MRI studies showing a range of findings.7

  • Lesions that correlate with NMOSD are frequently periependymal lesions located around the cerebral aqueduct and third and fourth ventricles, including regions of the thalamus, hypothalamus, and brainstem, where AQP4 is highly expressed. These types of periaqueductal lesions are common to NMOSD, but they are rarely seen in the brains of MS patients.
  • Lesions forming in the APS, the emesis-inducing area of the brain, are associated with common early symptoms of NMOSD including nausea, vomiting, and intractable hiccups.7  Like the attacks they cause, lesions in NMOSD tend to be transient; therefore, MRI should be performed promptly at the time patients present with symptoms so that the lesions can be visualized.7
  • Additional brain abnormalities include large subcortical white matter lesions greater than 3 centimeters in size; these are most commonly observed in patients with AQP4-seropositive NMOSD.7
  •  Vision loss is an early sign of NMOSD, and the associated optic nerve lesions are readily distinguishable from those of patients with MS. In MS the optic lesions are shorter, unilateral, and more anterior. Optic nerve lesions in NMOSD extend over more than half of the posterior optic nerve, often into the optic chiasm.7

Summary

The feature of NMOSD that most clearly defines it as separate from other demyelinating diseases is seropositivity to AQP4, although not all patients with NMOSD are AQP4 seropositive. In patients who are AQP4 seronegative or those in whom AQP4 status is unknown, MRI studies are essential to support the diagnosis of NMOSD, along with a more stringent requirement that at least 2 core characteristics be present. 

References

1. Huda S, Whittam D, Bhojak M, et al. Neuromyelitis optica spectrum disorders. Clin Med (Lond). 2019;19:169-176. doi:10.7861/clinmedicine.19-2-169

2. Czarnecka D, Oset M, Karlińska I, Stasiołek M. Cognitive impairment in NMOSD – More questions than answers. Brain Behav. 2020;10(11):e01842. doi:10.1002/brb3.1842

3. Jarius S, Wildemann B. The history of neuromyelitis optica. J Neuroinflammation. 2013;10:8. doi:10.1186/1742-2094-10-8

4. Wingerchuk DM, Banwell B, Bennett JL, et al; International Panel for NMO Diagnosis. International consensus diagnostic criteria for neuromyelitis optica spectrum disorders. Neurology. 2015;85(2):177-189. doi:10.1212/WNL.0000000000001729

5. Papp V, Magyari M, Aktas O, et al. Worldwide incidence and prevalence of neuromyelitis optica: a systematic review. Neurology. 2021;96:59-77. doi:10.1212/WNL.0000000000011153

6. Hor JY, Asgari N, Nakashima I, et al; on behalf of the Guthy-Jackson Charitable Foundation International Clinical Consortium for NMOSD. Epidemiology of neuromyelitis optica spectrum disorder and its prevalence and incidence worldwide. Front Neurol. 2020;11:501. doi:10.3389/fneur.2020.00501

7. Solomon JM, Paul F, Chien C, Oh J, Rotstein DL. A window into the future? MRI for evaluation of neuromyelitis optica spectrum disorder throughout the disease course. Ther Adv Neurol Disord. 2021;14:1-18. doi:10.1177/17562864211014389

8. Flanagan EP, Weinshenker BG, Krecke KN, et al. Short myelitis lesions in aquaporin-4-IgG-positive neuromyelitis optica spectrum disorders. JAMA Neurol. 2015;72(1):81-87. doi:10.1001/jamaneurol.2014.2137

9. Ratchford JN, Quigg ME, Conger A, et al. Optical coherence tomography helps differentiate neuromyelitis optica and MS optic neuropathies. Neurology. 2009;73(4):302-308. doi:10.1212/WNL.0b013e3181af78b8

10. Naismith RT, Tutlam NT, Xu J, et al. Optical coherence tomography differs in neuromyelitis optica compared with multiple sclerosis. Neurology. 2009;72:1077-1082. doi:10.1212/01.wnl.0000345042.53843.d5

11. Pittock SJ, Lucchinetti CF. Neuromyelitis optica and the evolving spectrum of autoimmune aquaporin-4 channelopathies: a decade later. Ann NY Acad Sci. 2016;1366:20-39. doi:10.1111/nyas.12794

12. Akaishi T, Nakashima I, Sato DK, Takahashi T, Fujihara K. Neuromyelitis optica spectrum disorders. Neuroimaging Clin N Am. 2017;27:251-265. doi:10.1016/j.nic.2016.12.010

13. Blanc F, Zéphir H, Lebrun C, et al. Cognitive functions in neuromyelitis optica. Arch Neurol. 2008;65(1):84-88. doi:10.1001/archneurol.2007.16

14. Moore P, Methley A, Pollard C, et al. Cognitive and psychiatric comorbidities in neuromyelitis optica. J Neurol Sci. 2016;360:4-9. doi:10.1016/j.jns.2015.11.031

15. Narayan R, Simpson A, Fritsche K, et al. MOG antibody disease: a review of MOG antibody seropositive neuromyelitis optica spectrum disorder. Mult Scler Relat Disord. 2018;25:66-72. doi:10.1016/j.msard.2018.07.025

16. Weinshenker BG, Wingerchuk DM. Neuromyelitis spectrum disorders. Mayo Clin Proc. 2017;92(4):663-679. doi:10.1016/j.mayocp.2016.12.014

17. Jarius S, Ruprecht K, Wildemann B, et al. Contrasting disease patterns in seropositive and seronegative neuromyelitis optica: a multicentre study of 175 patients. J Neuroinflammation. 2012;9:14. doi:10.1186/1742-2094-9-14

Posted by Haymarket’s Clinical Content Hub. The editorial staff of Clinical Pain Advisor had no role in the preparation of this content.

Reviewed June 2021

Fatigue in Multiple Sclerosis: Providing an Effective Diagnostic Approach

Fatigue is one of the most commonly reported and debilitating symptoms of multiple sclerosis (MS), affecting an estimated 70% to 90% of patients, and is the major contributor to poor health perception.1-3 In a survey of 20 neurologists involving 198 patients with MS, fatigue was reported to be the most common symptom of the disease (Figure 1).4



Despite its prevalence and significant impact on quality of life, MS-related fatigue remains one of the least understood MS symptoms and among the most difficult to diagnose and manage. The complexity of the pathophysiologic mechanisms of fatigue, the subjectivity of its presentation, and the myriad comorbidities that can result in secondary fatigue contribute to significant diagnostic challenges.

Although more than 250 fatigue diagnostic tools have been developed,5 most are not validated for patients with MS or designed to assess multidimensional fatigue related to MS. Understanding the pathophysiologic mechanisms of MS fatigue provides a rational basis for the differential diagnosis of MS fatigue. This article explores current understanding of the pathophysiologic mechanisms of MS fatigue and its differential diagnosis, both of which are critical for individualized fatigue management.

MS-related Fatigue: Pathophysiologic Mechanism

MS-related fatigue is clinically recognized as primary fatigue (associated with the MS disease process) and secondary fatigue (associated with disease complications and comorbidities, such as spasticity, restless legs syndrome, sleep disorders, depression, and pain). The pathophysiology of primary and secondary MS-related fatigue is complex, with each thought to be distinct but interrelated by factors such as musculoskeletal problems, sleep disorders, medication adverse effects, and altered endocrine function (Figure 2).6 Clinicians should recognize that optimal fatigue management requires treating both primary and secondary MS fatigue. Effectively managing MS complications and comorbidities can also manage secondary fatigue; primary fatigue must also be managed, although it is more challenging to diagnose.



The commonly proposed pathophysiology of primary fatigue in MS is thought to involve the thalamus, brain and spinal cord inflammation, cytokine release, and neuroendocrine and autonomic abnormalities associated with gray- and white-matter neuronal lesions.7-9 Brain structural changes and neurodegeneration detected with advanced quantitative magnetic resonance imaging correlate with development of fatigue in patients with MS.10-12 Brain inflammatory activity correlating with waxing and waning of the disease and variation in fatigue symptoms over time also supports inflammation as an essential contributor to primary MS fatigue. For example, disease relapses have been associated with increased fatigue and reduced health-related quality of life, and MS treatment has been associated with reduced fatigue.13,14

However, the link between inflammatory activity and fatigue has not been unequivocally demonstrated. Although some studies have shown correlation between fatigue severity and inflammatory disease activity, others have not.15 Nevertheless, recognizing that fatigue in a patient with MS has a primary and secondary cause should raise clinical suspicion to manage MS complications and comorbidities, and underscores the importance of using tools that can differentially diagnose primary fatigue.

Barriers to a Diagnosis of MS

Diagnosing primary MS fatigue is often difficult for most clinicians. A contributing factor to this challenge is the multidimensional presentation of MS fatigue, which can manifest as physical, cognitive, and psychosocial fatigue. Fatigue symptoms vary from one patient to the next and over time, and a diagnostic tool validated to capture its complexity is lacking.

“Some of the factors that impact the differential diagnosis of MS fatigue [are] the variability of the assessment tools [which is] not directly correlated with clinical outcomes,” said Stacie Hudgens, Chief Executive Officer and Strategic Lead at Clinical Outcomes Solutions. “The lack of correlation to disease severity makes it difficult to predict fatigue outcomes, which then contributes to the challenge of differential diagnosis.”

Also a contributing factor are the criteria by which fatigue is defined, which have included16:

  • Reduction in performance following either prolonged or unusual exertion, together with feelings of sensory, motor, cognitive, or subjective fatigue;
  • Subjective lack of physical or mental energy perceived by the patient or caregiver as interfering with usual and desired activities;
  • Reversible motor and cognitive impairment, with reduced motivation and desire to rest; such impairment can appear spontaneously or be brought on by mental or physical activity, humidity, acute infection, or food ingestion;
  • Perception of decreased mental or physical energy that might restrict routine daily activities; and
  • Failure to initiate or sustain attentional tasks (mental or cognitive fatigue) and physical activities (physical fatigue).

Core elements of these definitions are subjective and difficult to quantify. In the absence of a standardized definition, diagnosing fatigue in patients with MS is complex and challenging. Self-reported fatigue questionnaires are commonly used diagnostic tools in clinical practice and research17; however, MS-related fatigue is considered a multidimensional symptom that includes physical fatigue, cognitive fatigue, and psychosocial fatigue, all of which should be accommodated in the assessment and in treatment decisions. Treatment decisions made from diagnostic evaluations using the Modified Fatigue Impact Scale (MFIS), Fatigue Severity Scale (FSS-9), or Short Form-36 (SF-36) vitality scale appear to be suboptimal because these tools assess fatigue severity but not the multiple dimensions of fatigue.17

Assessing MS fatigue using patient-reported outcomes (PRO) recognizes the subjective nature of fatigue and its unique impact on each patient. A PRO instrument with demonstrated consistency, reliability, and validity was proposed in quality-of-care measures for MS, emphasized by US Food and Drug Administration PRO guidance for outcome measurement in clinical trials, and recommended in Clinical Outcomes Assessments of the International Society for Pharmacoeconomics and Outcomes Research.18-20 However, PRO instruments that have been used to measure fatigue in patients with MS have shortcomings with regard to validity, reliability, and sensitivity. For instance, the 9-item FSS-9 and the 21-item MFIS, tools that are commonly used as outcome measures in MS, have been found to have poor discrimination with bias for variables such as age and cannot be used to generate a single overall fatigue score.21,22

Tools for the Differential Diagnosis of MS Fatigue

Historically, scales used to assess fatigue in patients with MS were developed for other chronic medical conditions, such as chronic fatigue syndrome and systemic lupus erythematosus. Generally, these scales primarily quantified fatigue or assessed its impact on various functions and did not comprehensively assess the multidimensional contributors of MS-related fatigue.9

Existing diagnostic tools, such as the FSS-9 and MFIS, are limited by their multidimensionality and cannot be used to assess fatigue across various forms of MS. A PRO instrument validated in specific MS subtypes will enable a more specific, accurate, and individualized fatigue assessment. A modified PRO instrument, the Fatigue Symptoms and Impacts Questionnaire-Relapsing Multiple Sclerosis (FSIQ-RMS), was designed to address limitations of existing instruments used to assess MS-specific fatigue. The instrument was evaluated in patients with relapsing-remitting multiple sclerosis (RRMS), progressive relapsing multiple sclerosis (PRMS), and relapsing secondary progressive multiple sclerosis (RSPMS).23 FSIQ-RMS, which includes 7 symptom and 13 impact items (in 3 impacts subdomains: physical, cognitive and emotional, and coping), is an instrument with demonstrated content and measurement validity for MS fatigue.23

“The FSIQ-RMS is a fatigue-specific patient-reported outcome measure, designed with patient input, to cover the full spectrum of mental and physical fatigue severity in patients with MS, including cognitive, emotional, and coping impacts [of fatigue],” Ms Hudgens said. “[The FSIQ-RMS] is a valid and reliable assessment of a patient’s fatigue severity that was developed from direct patient interviews and patient surveys.”

FSIQ-RMS has been assessed only in patients with RRMS, PRMS, and RSPMS subtypes; as such, it might not be applicable in patients with other MS subtypes. However, evidence suggests that the FSIQ-RMS is a tool clinicians can consider to diagnose MS fatigue.

Whether a multidimensional assessment of MS fatigue is essential for diagnostic evaluation and treatment decisions was explored in a study by Beckerman and colleagues.17 The researchers investigated whether treatment indications for severe primary MS fatigue should be based on the various dimensions of fatigue or whether a unidimensional assessment can assess perceived fatigue in patients with MS. The 4 fatigue instruments evaluated were the MFIS, FSS, SF-36, and the Checklist of Individual Strengths (CIS20r) fatigue subscale.17 The CIS20r is a multidimensional questionnaire comprising 20 items in 4 fatigue dimensions and related behavioral aspects, including:

  • The subjective experience of fatigue (8 items);
  • A reduction in motivation (4 items);
  • A reduction of physical activity (3 items); and
  • A reduction in concentration (5 items).

In the analysis conducted by Beckerman et al, those 4 fatigue instruments appear to measure different fatigue constructs. The researchers also argue that no available study has shown that a dimension-specific treatment of fatigue leads to better outcomes. Based on their findings, they suggest that a single simple fatigue scale, such as the CIS20r fatigue subscale, is sufficient for the diagnosis of fatigue, as well as for the initiation of treatment.17 In terms of clinical practice, Beckerman and colleagues suggest that there is, as yet, no reason to measure multidimensional aspects of fatigue in primary MS-related fatigue.

Involving the Patient in the Differential Diagnosis
Fatigue associated with MS is more than the tiredness that accompanies exertion or poor sleep and can be difficult for a patient to describe. Having patients communicate their fatigue is essential to the diagnostic workup, subsequent differential diagnosis, and optimal management. A visual from the MS International Federation (Figure 3) that describes different MS fatigue levels might help a patient describe their fatigue effectively to their healthcare provider.24



Manifestations of MS Fatigue
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Manifestations of MS Fatigue
MS fatigue tends to become worse as the day progresses; appears suddenly compared to fatigue due to exertion, such as with exercise, or to poor sleep; and is aggravated by heat and humidity.

Summary
Fatigue is one of the most common and debilitating MS symptoms, yet it remains challenging for clinicians to effectively diagnose. Commonly used diagnostic tools such as the MFIS, FSS-9, and SF-36 lack specificity and validity to assess the multiple dimensions of MS fatigue. A patient-reported outcome measure, such as FSIQ-RMS, incorporates patient input in its design. The tool assesses the spectrum of mental and physical fatigue severity in patients with MS. Optimal fatigue diagnosis and management might require clinicians to (1) use visual cues to guide patients with MS to communicate their fatigue symptoms and (2) maintain a high index of suspicion for MS complications and comorbidities often associated with secondary fatigue, which must also be managed.
 
Disclosures
Stacie Hudgens, MA, is an independent outcomes researcher with a reported affiliation to Clinical Outcomes Solutions.

References


1. Costello K, Harris C. Differential diagnosis and management of fatigue in multiple sclerosis: considerations for the nurse. J Neurosci Nurs. 2003;35(3):139-148. doi:10.1097/01376517-200306000-00003
2. Bakshi R. Fatigue associated with multiple sclerosis: diagnosis, impact and management. Mult Scler. 2003;9(3):219-227. doi:10.1191/1352458503ms904oa
3. Green R, Cutter G, Friendly M, Kister I. Which symptoms contribute the most to patients’ perception of health in multiple sclerosis? Mult Scler J Exp Transl Clin. 2017;3(3):2055217317728301. doi:10.1177/2055217317728301
4. Ziemssen T, Piani-Meier D, Bennett B, et al. A physician-completed digital tool for evaluating disease progression (multiple sclerosis progression discussion tool): validation study. J Med Internet Res. 2020;22(2):e16932. doi:10.2196/16932
5. Hjollund NH, Andersen JH, Bech P. Assessment of fatigue in chronic disease: a bibliographic study of fatigue measurement scales. Health Qual Life Outcomes. 2007;5:12. doi:10.1186/1477-7525-5-12
6. Carter JL. Fatigue in patients with multiple sclerosis. Practical Neurology. 2018 July/August:43-46. https://practicalneurology.com/articles/2018-july-aug/fatigue-in-patients-with-multiple-sclerosis/pdf. Accessed December 28, 2020.
7. Capone F, Collorone S, Cortese R, Di Lazzaro V, Moccia M. Fatigue in multiple sclerosis: the role of thalamus. Mult Scler. 2020;26(1):6-16. doi:10.1177/1352458519851247
8. Manjaly Z-M, Harrison NA, Critchley HD, et al. Pathophysiological and cognitive mechanisms of fatigue in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2019;90(6):642-651. doi:10.1136/jnnp-2018-320050
9. Braley TJ, Chervin RD. Fatigue in multiple sclerosis: mechanisms, evaluation, and treatment. Sleep. 2010;33(8):1061-1067. doi:10.1093/sleep/33.8.1061
10. Arm J, Ribbons K, Lechner-Scott J, Ramadan S. Evaluation of MS related central fatigue using MR neuroimaging methods: scoping review. J Neurol Sci. 2019;400:52-71. doi:10.1016/j.jns.2019.03.007
11. Patejdl R, Penner IK, Noack TK, Zettl UK. Multiple sclerosis and fatigue: a review on the contribution of inflammation and immune-mediated neurodegeneration. Autoimmun Rev. 2016;15(3):210-220. doi:10.1016/j.autrev.2015.11.005
12. Palotai M, Nazeri A, Cavallari M, et al. History of fatigue in multiple sclerosis is associated with grey matter atrophy. Sci Rep. 2019;9(1):14781. doi:10.1038/s41598-019-51110-2
13. Mäurer M, Comi G, Freedman MS, et al. Multiple sclerosis relapses are associated with increased fatigue and reduced health-related quality of life – a post hoc analysis of the TEMSO and TOWER studies. Mult Scler Relat Disord. 2016;7:33-40. doi:10.1016/j.msard.2016.02.012
14. Svenningsson A, Falk E, Celius EG, et al; Tynergy Trial Investigators. Natalizumab treatment reduces fatigue in multiple sclerosis. Results from the TYNERGY trial; a study in the real life setting. PLoS One. 2013;8(3):e58643. doi:10.1371/journal.pone.0058643
15. Chalah MA, Ayache SS. Is there a link between inflammation and fatigue in multiple sclerosis? J Inflamm Res. 2018;11:253-264. doi:10.2147/JIR.S167199
16. Mills RJ, Young CA. A medical definition of fatigue in multiple sclerosis. QJM. 2008;101(1):49-60. doi:10.1093/qjmed/hcm122
17. Beckerman H, Eijssen IC, van Meeteren J, Verhulsdonck MC, de Groot V. Fatigue profiles in patients with multiple sclerosis are based on severity of fatigue and not on dimensions of fatigue. Sci Rep. 2020;10(1):4167. doi:10.1038/s41598-020-61076-1
18. Rae-Grant A, Bennett A, Sanders AE, Phipps M, Cheng E, Bever C. Quality improvement in neurology: multiple sclerosis quality measures: executive summary. Neurology. 2015;85(21):1904-1908. doi:10.1212/WNL.0000000000001965
19. US Food and Drug Administration. Roadmap to patient-focused outcome measurement in clinical trials (text version). https://www.fda.gov/drugs/drug-development-tool-ddt-qualification-programs/roadmap-patient-focused-outcome-measurement-clinical-trials-text-version. October 8, 2015. Accessed January 7, 2021.
20. Walton MK, Powers JH 3rd, Hobart J, et al; International Society for Pharmacoeconomics and Outcomes Research Task Force for Clinical Outcomes Assessment. Clinical outcome assessments: conceptual foundation – report of the ISPOR clinical outcomes assessment – emerging good practices for outcomes research task force. Value Health. 2015;18(6):741-752. doi:10.1016/j.jval.2015.08.006
21. Mills RJ, Young CA, Nicholas RS, Pallant JF, Tennant A. Rasch analysis of the Fatigue Severity Scale in multiple sclerosis. Mult Scler. 2009;15(1):81-87. doi:10.1177/1352458508096215
22. Mills RJ, Young CA, Pallant JF, Tennant A. Rasch analysis of the Modified Fatigue Impact Scale (MFIS) in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2010;81(9):1049-1051. doi:10.1136/jnnp.2008.151340
23. Hudgens S, Schüler R, Stokes J, Eremenco S, Hunsche E, Leist TP. Development and validation of the FSIQ-RMS: a new patient-reported questionnaire to assess symptoms and impacts of fatigue in relapsing multiple sclerosis. Value Health. 2019;22(4):453-466. doi:10.1016/j.jval.2018.11.007
24. Fatigue. London, England: Multiple Sclerosis International Federation. https://www.msif.org/about-ms/symptoms-of-ms/fatigue/.  Accessed December 28, 2020. 

Posted by Haymarket’s Clinical Content Hub. The editorial staff of Neurology Advisor had no role in this content’s preparation.
 
                                                                                                                     

  Reviewed January 2021