In search of distinct MS-related fatigue subtypes: results from a multi-cohort analysis in 1.403 MS patients

Self-Report Measures of Fatigue for People With Multiple Sclerosis: A Systematic Review

BACKGROUND AND PURPOSE

The symptom of fatigue impairs function in people with multiple sclerosis (MS). Choosing appropriate measures to assess fatigue is challenging. The purpose of this article is to report the findings of a systematic review of patient-reported fatigue measures for people with MS.

METHODS

PubMed, CINAHL, and Embase databases were searched through January 2020 using terms related to fatigue and MS. Studies were included if the sample size was 30 or more or smaller samples if adequately powered, and if information about measurement characteristics (ie, test-retest reliability, content validity, responsiveness, interpretability, or generalizability) of the measure(s) could be extracted. Study quality was appraised with the 2-point COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. Data about measurement characteristics, psychometrics, and clinical utility were extracted and results were synthesized.

RESULTS

Twenty-four articles met inclusion criteria with information about 17 patient-reported fatigue measures. No studies had critical methodologic flaws. Measurement characteristic data were not available for all measures. Clinical utility varied in time to complete and fatigue domains assessed.

DISCUSSION AND CONCLUSIONS

Five measures had data pertaining to all properties of interest. Of these, only the Modified Fatigue Impact Scale (MFIS) and Fatigue Severity Scale (FSS) had excellent reliability, responsiveness data, no notable ceiling/floor effects, and high clinical utility. We recommend the MFIS for comprehensive measurement and the FSS for screening of subjective fatigue in people with MS.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A443 ).

Characterizing fatigue phenotypes with other symptoms and clinically relevant outcomes among people with multiple sclerosis

PURPOSE

Fatigue is a common symptom of multiple sclerosis (MS) and can adversely affect all aspect of quality of life. The etiology of fatigue remains unclear, and its treatments are suboptimal. Characterizing the phenotypes of fatigued persons with MS may help advance research on fatigue's etiology and identify ways to personalize fatigue interventions to improve quality of life. The purpose of this study was to identify fatigue phenotypes; examine phenotype stability overtime; and characterize phenotypes by health and function, social and environmental determinants, psychosocial factors, and engagement in healthy behaviors.

METHODS

We conducted a longitudinal study over a 3-month period with 289 fatigued participants with MS. To identify fatigue phenotypes and determine transition probabilities, we used latent profile and transition analyses with valid self-report measures of mental and physical fatigue severity, the mental and physical impact of fatigue, depression, anxiety, and sleep quality. We used ANOVAs and effect sizes to characterize differences among phenotypes.

RESULTS

The best fitting model included six subgroups of participants: Mild Phenotype, Mild-to-Moderate Phenotype, Moderate-to-Severe Phenotype, Severe Phenotype, Fatigue-dominant Phenotype, and Mental Health-dominant Phenotype. The transition analysis indicated that phenotypic membership was highly stable. Variables with a large eta squared effect size included environmental barriers, self-efficacy, and fatigue catastrophizing.

CONCLUSION

These results indicate that the magnitude of fatigue experienced may be more important to consider than the type of fatigue when characterizing fatigue phenotypes. Future research should explore whether tailoring interventions to environmental barriers, self-efficacy, and fatigue catastrophizing reduce the likelihood of transitioning to a more severe phenotype.

The pathophysiology of motor fatigue and fatigability in multiple sclerosis

Multiple Sclerosis (MS) is a heterogeneous immune mediated disease of the central nervous system (CNS). Fatigue is one of the most common and disabling symptom of MS. It interferes with daily activities on the level of cognition and motor endurance. Motor fatigue can either result from lesions in cortical networks or motor pathways (“primary fatigue”) or it may be a consequence of detraining with subsequent adaptions of muscle and autonomic function. Programmed exercise interventions are used frequently to increase physical fitness in MS-patients. Studies investigating the effects of training on aerobic capacity, objective endurance and perceived fatigability have yielded heterogenous results, most likely due to the heterogeneity of interventions and patients, but probably also due to the non-uniform pathophysiology of fatigability among MS-patients. The aim of this review is to summarize the current knowledge on the pathophysiology of motor fatigability with special reference to the basic exercise physiology that underlies our understanding of both pathogenesis and treatment interventions.

The Association Between Actigraphy-Derived Behavioral Clusters and Self-Reported Fatigue in Persons With Multiple Sclerosis: Cross-sectional Study

Background

Persons with multiple sclerosis frequently report increased levels of fatigue and fatigability. However, behavioral surrogates that are strongly associated with self-reports are lacking, which limits research and treatment.

Objective

The aim of this study was to derive distinct behavioral syndromes that are reflected by self-reports concerning fatigue and fatigability.

Methods

We collected actigraphic data of 30 persons with multiple sclerosis over a period of 1 week during an inpatient stay at a neurorehabilitation facility. Further, participants completed the German fatigue severity scale. A principal component analysis of actigraphic parameters was performed to extract the latent component levels of behaviors that reflect fatigue (quantity of activity) and fatigability (fragmentation of activity). The resulting components were used in a cluster analysis.

Results

Analyses suggested 3 clusters, one with high activity (d=0.65-1.57) and low clinical disability levels (d=0.91-1.39), one with high levels of sedentary behavior (d=1.06-1.58), and one with strong activity fragmentation (d=1.39-1.94). The cluster with high levels of sedentary behavior further revealed strong differences from the other clusters concerning participants’ reported levels of fatigue (d=0.99-1.28).

Conclusions

Cluster analysis data proved to be feasible to meaningfully differentiate between different behavioral syndromes. Self-reports reflected the different behavioral syndromes strongly. Testing of additional domains (eg, volition or processing speed) and assessments during everyday life seem warranted to better understand the origins of reported fatigue symptomatology.

Disentangling self-reported fatigue, depression, and cognitive impairment in people with multiple sclerosis

BACKGROUND

Fatigue is a common problem among people with multiple sclerosis (MS) and can have a negative effect on mental, physical, and social function. Self-reported measures of MS fatigue are often operationalized as a multi-dimensional symptom. However, questions remain about how best to account for the multi-dimensional aspects of self-reported fatigue and whether these aspects are distinct entities. Thus, the purpose of this study was to explore the overlap and distinctions between self-reported measures of the severity and impact of fatigue, between mental and physical fatigue, and between mental fatigue, depressive symptoms, and cognitive impairment.

METHODS

An observational study was conducted with 289 participants with MS . The questionnaires were the Unidimensional Fatigue Impact Scale (UFIS), the Chalder Fatigue Scale (CFS), the Fatigue Scale for Motor and Cognitive Functions (FSMC), the Multiple Sclerosis Neuropsychological Screening Questionnaire (MSNSQ), and the Quality of Life in Neurological Disorders short form for depression (Neuro-QoL). Spearman's correlation coefficient was used to examine the bivariate correlations between composite and subscale scores. Exploratory structural equation modeling (ESEM) was used to determine the factor structure under a pre-specified number of factors to retain in the modeling of multiple items across questionnaires and examine model fit. Subsequently for poor fitting models in an iterative procedure to determine a better fitting multidimensional model, we posited a bifactor confirmatory factor analysis model.

RESULTS

The bivariate correlation analysis revealed that subscales from the same questionnaire measuring different aspects of fatigue had the highest correlations (r = 0.61-0.68), subscales from different questionnaires measuring the same aspect of fatigue had the next highest correlations (r = 0.43-0.60), and subscales from different questionnaires measuring different aspects of fatigue had the lowest correlations (r = 0.34-0.40). Bifactor models with a general fatigue factor and subdomains pertaining to impact, severity, and mental and physical fatigue had relatively good model fits compared to models omitting the subdomains. However, an ESEM model using subscales from the CFS and FSMC fit poorly and did not adequately identify separate factors for mental and physical fatigue. An ESEM model with separate factors for self-reported mental fatigue, depressive symptoms, and cognitive impairment was a good fit.

CONCLUSIONS

The working study hypothesis that fatigue constructs would be moderately correlated yet distinct entities was generally supported by the results of the study. However, we found that our hypothesized separation into a latent dimension existed only when the items or subscales came from the same questionnaire, in which case their level of specificity in terms of target, action, context, and time elements for measuring fatigue were consistent. The implications for the principle of compatibility in measuring self-reported MS fatigue are discussed.

Sensorimotor function does not predict quality of life in persons with multiple sclerosis

Quality of life (QOL) has been reported to be reduced in persons with multiple sclerosis. Further, associations between QOL and the clinical severity of the disease as well as sensorimotor function were shown. We reinvestigated impacting factors on QOL by the additional assessment of depression, fatigue, satisfaction with life, and a battery of end-effector based assessments of sensorimotor functioning. Models of multiple linear regression revealed everyday life activity limitations to be the driving factor within the used questionnaire and no association with sensorimotor tests, but depression, fatigue, and satisfaction with life. We conclude that either psycho-emotional coping and adaptability are the dominant determinant of QOL or that QOL is in need of a quantitative and objective reconceptualization.

Association of Fatigue Severity With Maladaptive Coping in Multiple Sclerosis: A Data-Driven Psychodynamic Perspective

Fatigue in persons with multiple sclerosis (PwMS) is severely disabling. However, the underlying mechanisms remain incompletely understood. Recent research suggests a link to early childhood adversities and psychological trait variables. In line with these studies, this paper took a psychodynamic perspective on MS-fatigue. It was hypothesized that fatigue could represent a manifestation of maladaptive coping with intense emotions. The schema therapeutic mode model served as a theoretical and empirically validated framework, linking psychodynamic theory and empirical research methods. The study was based on a data set of N = 571 PwMS that has also served as the basis for another publication. Data was collected online. The Schema Mode Inventory was used to quantify regulatory strategies to cope with emotionally stressful experiences. In addition, depressive symptoms (Beck's Depression Inventory - FastScreen), physical disability (Patient Determined Disease Steps), alexithymia (Toronto Alexithymia Scale-26), adverse childhood experiences (Childhood Trauma Questionnaire), and self-reported fatigue (Fatigue Scale for Motor and Cognitive Functions) were assessed. Latent profile analysis revealed three distinct groups of PwMS, based on their coping mode profiles: (1) PwMS with low maladaptive coping, (2) PwMS with avoidant/submissive coping styles, and (3) PwMS with avoidant/overcompensatory coping styles. Multivariate comparisons showed no significant difference in physical disability across the three groups. However, heightened levels of self-reported fatigue and depression symptoms occurred in PwMS with maladaptive coping styles. A path model uncovered that self-reported fatigue was robustly related to physical disability (β = 0.33) and detached/avoidant coping (Detached Protector; β = 0.34). There was no specific relation between any of the maladaptive coping modes and depression symptoms. Detached/avoidant coping was in turn predicted by childhood emotional abuse and neglect. The results indicate that childhood adversity and detached/avoidant coping styles may be associated with variability in MS-fatigue severity: PwMS that resort to detached/avoidant coping in response to negative emotions also tend to report heightened levels of fatigue, although they do not differ in their perceived disability from PwMS with low levels of fatigue and maladaptive coping. A link between MS-fatigue and the psychodynamic traumatic conversion model is discussed. The implications of these findings for therapeutic interventions require further study.

Outcome measures for physical fatigue in individuals with multiple sclerosis: a systematic review

INTRODUCTION

Physical fatigue can be a common reason for early retirement or sick leave since it appears in the earliest stages of multiple sclerosis (MS). Therefore, a prompt and accurate diagnosis is essential. This systematic review aims to identify and describe the instruments used to assess physical fatigue in MS patients with consideration for the languages used to validate the instruments and their methodological qualities.

AREA COVERED

This study has been carried out through 'Medline,' 'Scopus,' 'Cinhal,' and 'Web of Science' databases for all the papers published before 24 January 2020. Three independent authors have chosen the eligible studies based upon pre-set criteria of inclusion. Data collection, data items, and assessment of the risk of bias: the data extraction approach was chosen based on the Cochrane Methods. For data collection, the authors followed the recommendations from the COSMIN initiative. Study quality and risk of bias were assessed using the COSMIN Check List.

EXPERT OPINION

119 publications have been reviewed. The 45 assessment scales can be divided into specific scales for physical fatigue and specific scales for MS. The most popular tools are the Fatigue Severity Scale and the Modified Fatigue Impact Scale.

Assessing fatigue in multiple sclerosis: Psychometric properties of the five-item Modified Fatigue Impact Scale (MFIS-5)

Fatigue in multiple sclerosis is a key symptom associated with work-related problems and poor quality of life outcomes. The five-item Modified Fatigue Impact Scale is a brief self-assessment tool for measuring the impact of fatigue on cognitive, physical and psychosocial function. A non-interventional, cross-sectional study was conducted to assess dimensionality and item characteristics of the five-item Modified Fatigue Impact Scale in multiple sclerosis. A total of 302 subjects were studied. Mokken analysis found the five-item Modified Fatigue Impact Scale is a strong one-dimensional scale (overall scalability index H = 0.67) with high reliability (Cronbach’s alpha = 0.90). The confirmatory factor analysis model confirmed the one-dimensional structure (comparative fit index = 1.0, root-mean-square error of approximation = 0.035). Samejima’s model fitted well as an unconstrained model with different item difficulties. The five-item Modified Fatigue Impact Scale shows appropriate psychometric characteristics and may constitute a valuable and easy-to-implement addition to measure the impact of fatigue in clinical practice.