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rev bras reumatol. 2017;xxx(xx):xxx-xxx
REVISTA BRASILEIRA DE REUMATOLOGIA
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Original article
Measuring fatigue with multiple instruments in a Brazilian cohort of early rheumatoid arthritis patients
Leonardo Rios Diniza'*, Sandor Balsamoa, Talita Yokoy de Souzab,
Luciana Feitosa Munizb, Wagner Rodrigues Martinsc, Licia Maria Henrique da Motaa,b
a Univesidade de Brasilia (UnB), Faculdade de Medicina, Programa de Pós-Graduagao em Ciencias Médicas, Brasilia, DF, Brazil b Univesidade de Brasilia (UnB), Hospital Universitário de Brasilia, Servico de Reumatologia, Brasilia, DF, Brazil c Univesidade de Brasilia (UnB), Faculdade de Fisioterapia, Brasilia, DF, Brazil
article info
abstract
Article history: Objective: To assess the prevalence of fatigue in a Brazilian population with early rheumatoid
Received 13 October 2016 arthritis using multiple instruments, and the predictors of these instruments by differents
Accepted 26 April 2017 independent variables.
Available online xxx Methods:Cross-sectional study with direct interview and medical records review. Fatigue,
__dependent variable, was assessed using eight instruments: Profile of Mood States (POMS),
Keyu)0rdS:Multidimensional Assessment of Fatigue scale (MAF), Fatigue Severity Scale (FSS), Bristol Disability Rheumatoid Arthritis Fatigue Multidimensional Questionnaire (BRAF-MDQ), Numerical Rat-
Fatigue ing Scales (BRAF-NRS), Short-form Survey 36 (SF-36), Functional Assessment of Chronic
Rheumatoid arthritis Illness Therapy Fatigue Scale (FACIT-F) and Visual Analogic Scale for Fatigue (VASf). Inde-
pendent variables: sociodemographic, clinical and serological, were measured using medical records and direct interview. Disability and disease activity were assessed using the Health Assessment Questionnaire (HAQ) and disease activity assessed using the Disease Activity Score 28 joints (DAS28). The scores of scales demonstrated the level of fatigue and multiple linear regression method used in statistical analysis to demonstrate prediction models. Results: A total of 80 patients was assessed, and 57 reported clinically relevant fatigue (VASf>2), representing 71.25% prevalence point (51 women [89.5%], mean age 48.35 ±15 years, and mean disease duration of 4.92 ±3.8 years). Eight predictive models showed statistical significance, one for each fatigue instrument. The highest coefficient of determination (R2) was 56% for SF-36 and the lowest (R2 = 21%) for FSS. The HAQ was the only independent variable to predict fatigue on all instruments.
Conclusion:Clinically relevant fatigue is a highly prevalent symptom and is mostly predicted by disability and age in the population assessed.
© 2017 Elsevier Editora Ltda. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
* Corresponding author. E-mail: lrdiniz@gmail.com (L.R. Diniz). http://dx.doi.org/10.1016Zj.rbre.2017.05.004
2255-5021/© 2017 Elsevier Editora Ltda. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
rev bras reumatol. 2017;xxx(xx):xxx-xxx
Mensuracao da fadiga com múltiplos instrumentos em uma coorte brasileira de pacientes com artrite reumatoide em fase inicial
Palavras-chave:
Incapacidade
Fadiga
Artrite reumatoide
resumo
Objetivo: Avaliar a prevalencia de fadiga em uma coorte brasileira de pacientes com artrite reumatoide em fase inicial com múltiplos instrumentos e os preditores desses instrumentos de acordo com diferentes variáveis independentes.
Métodos:Estudo transversal com entrevista direta e revisao de prontuários. A fadiga, a variável dependente, foi avaliada por meio de oito instrumentos: Profile of Mood States (POMS), Multidimensional Assessment of Fatigue Scale (MAF), Fatigue Severity Scale (FSS), Bristol Rheumatoid Arthritis Fatigue Multidimensional Questionnaire (BRAF-MDQ), Numerical Rating Scales (BRAF-NRS), Short-form Survey 36 (SF-36), Functional Assessment of Chronic Illness Therapy Fatigue Scale (Facit-F) e Escala Visual Analógica de fadiga (VASf). Variáveis independentes: mensuraram-se dados sociodemográficos, clínicos e sorológicos por meio da análise de prontuários e entrevista direta. A incapacidade e a atividade da doenca foram avaliadas com o Health Assessment Questionnaire (HAQ). A atividade da doenca foi avaliada com o Disease Activity Score 28 joints (DAS-28). As pontuacoes das escalas mostraram o nível de fadiga e usou-se o método de regressao linear múltipla na análise estatística para demonstrar os modelos de predicao.
Resultados:Avaliaram-se 80 pacientes; 57 relataram fadiga clinicamente relevante (VASf > 2), representaram uma prevalencia de 71,25% (51 mulheres [89,5%], média de 48,35 ± 15 anos e duracao média da doenca de 4,92 ±3,8 anos). Oito modelos preditivos mostraram significancia estatística, um para cada instrumento de fadiga. O maior coeficiente de determinacao (R2) foi de 56% para o SF-36 e o menor (R2 = 21%) foi para a FSS. O HAQ foi a única variável independente que predisse a fadiga em todos os instrumentos.
Conclusao: A fadiga clinicamente relevante é um sintoma altamente prevalente e é principalmente predita pela incapacidade e idade na populacao avaliada.
© 2017 Elsevier Editora Ltda. Este e um artigo Open Access sob uma licencia CC BY-NC-ND (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Introduction
Rheumatoid Arthritis (RA) is an autoimmune, chronic inflammatory disease characterized by joint swelling, joint tenderness, and destruction of the synovial joints that could lead to severe disability and premature mortality.1 RA affects between 0.5% and 1% of the general population and the impact on an individual's functional capacity results in a great economic burden to the individual and to society. It is estimated that 1.3 million individuals suffer from the disease in Brazil. Early RA is defined as the diagnosis given in the first weeks or months, usually less than 06 months, of joint symptoms or signs.1,2
Fatigue has grown in importance among patients with chronic diseases, despite of pain being a prevalent symptom. Fatigue is the enduring sensation of weakness, lack of energy, tiredness or exhaustion, and is reported by 40-80% of RA patients as their most disabling symptom. In addition, fatigue is not related to overexertion and is poorly relieved by rest; it is often multifactorial and prone to worsening by disease-related components, such as comorbid conditions, disease duration and/or activity, functional status, lifestyle factors, level of activity and inadequate social support.3-5
Studies have been conducted over the last 10-15 years to identify the characteristics of fatigue, its predictors, its effects, the correlation with several aspects of the disease, as well as
the development of new scales to measure fatigue, involving various domains. With respect to fatigue predictors and associated factors, only the study of Bianchi et al. assessed the correlation between fatigue and clinical and psychological variables. By using the Fatigue Assessment of Chronic Illness Therapy (FACIT-F), they observed that fatigue is an independent parameter, probably more related to psychological and functional impairments. They considered all RA patients, i.e., patients with early and established RA.6
According to Dupond, psychological fatigue or weariness is the most common pattern of fatigue, varying from 20% to 70% in RA patients, and that depression is the main source of fatigue in classic inflammatory rheumatic diseases.7 Minnock et al. conducted a longitudinal study with RA patients (n = 87) to assess the correlation of fatigue and disease activity. They observed that fatigue is not explained by disease activity as represented by the ACR core set outcomes, but is a behavioral variable with multifactorial influences, that vary with time of disease.8
Considering that fatigue predictors and associated factors are poorly investigated, or led to inconclusive directions, it is necessary to consider a study whose findings could predict fatigue across multiple independent variables. Furthermore, the use of patient-reported outcome measures (PROMs) assessing several domains may point out how fatigue affects each individual. In addition, studies drawing an early RA patient profile may also help develop more
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efficient approaches and public policies for rheumatoid arthritis.
Therefore, the aim of this study was to assess fatigue in a Brazilian population with early RA, using all the instruments available in Portuguese and assess the prediction models for fatigue by disease activity, disability, sociodemographic, clinical and serological variables.
Material and methods
Design
This is a cross-sectional study, carried out between May 2014 and May 2015, involving direct interview and review of the medical records of the patients diagnosed with early RA. This study was approved by the relevant ethics committee (University of Brasilia, School of Medicine, #897.320) and all patients signed a consent form.
Patients
The researchers assessed the patients of the Brazilian cohort of RA, an incident cohort of patients with early RA, and followed up in the Outpatient Rheumatology Clinic of the University Hospital of Brasilia - University of Brasilia.7
The inclusion criteria for this cohort comprises the following: early RA defined as the occurrence of articular symptoms, pain and edema with inflammatory pattern, associated or not with morning stiffness or other manifestations suggesting inflammatory joint disease (assessed by a single observer); at diagnosis, the disease duration more than 6 weeks, but less than 12 months, regardless of failure to meet the American College of Rheumatology (ACR) criteria.9
All selected patients retrospectively met the 2010 EULAR/ACR criteria.1 The patients admitted to this cohort are prospectively followed from the moment of diagnosis and receive the standard treatment regimen used in the service, including synthetic or biological disease-modifying anti-rheumatic drugs (DMARDs), according to their needs. Currently, there are patients with 11 years of follow up from initial diagnosis.
Exclusion criteria
Juvenile idiopathic arthritis, pregnancy and previously established diagnosis of any other collagenous diseases.
Data collection
The researchers collected information on gender, age, ethnicity, years of study, family income, marital status, number of dependents, disease duration and morning stiffness. Functional status was assessed using the Health Assessment Questionnaire (HAQ).10 Disease activity was assessed using the Disease Activity Score in 28 joints (DAS28)11 and pain was assessed using the global pain Visual Analog Scale (VASP).
Smoking habits, the number of comorbidities (fibromyal-gia, systemic arterial hypertension, dyslipidemia, diabetes mellitus, depression, hypothyroidism) and the number of
extra-articular symptoms, morning stiffness, erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were recorded. The researchers also assessed Swollen Joint Count in 28 joints (SJC28) and tender joint count in 28 joints (TJC28), body mass index (BMI), and collected subjective information on patients' mobility, daily living activities and pain/indisposition, age, ethnics, monthly income, years of study and marital status.
Fatigue assessment
The Profile of Mood States Fatigue/Inertia subscale (POMSF) is part of the POMS questionnaire, designed to measure mood states and their variation in psychiatric patients, but currently is used in several other conditions. It contains 7 items that range from 0 (not at all) to 4 (extremely) to form a fatigue score from 0 to 28. Higher scores imply greater fatigue.12
The Multidimensional Assessment of Fatigue Scale (MAF) was developed to measure multiple dimensions of fatigue in adults with RA. It covers 4 domains: severity, distress, interference with daily living activities, and frequency and change during the previous week. It contains 15 items to form an aggregated score, the Global Fatigue Index (GFI) and a 16th item that does not contribute to the GFI. The global fatigue index ranges from 0 to 50 and higher scores reflect greater pain.13
The Fatigue Severity Scale (FSS) was developed to assess fatigue in multiple sclerosis and systemic lupus erythemato-sus, but it has been used in RA analysis. It covers physical, social or cognitive effects of fatigue, organized in 9 items to produce a global score. The items are scored 1 (strongly disagree) to 7 (strongly agree), summed and then averaged to produce a global score. Higher scores represent greater fatigue severity, distress, or interference.14
The Bristol Rheumatoid Arthritis Fatigue Multidimensional Questionnaire (BRAF-MDQ) was developed to assess overall experience and impact of fatigue, and its dimensions. It contains 20 items, providing a total fatigue score (0-70) and 4 subscales scores for physical (0-22), living with (0-21), cognitive (0-15) and emotional fatigue (0-12); higher scores reflect greater severity.13
The Bristol Rheumatoid Arthritis Fatigue Numerical Rating Scales (BRAF-NRS) contains standardized numeric rating scales for measuring RA fatigue domains: Severity, Effect and Coping. Each scale scores 0-10, with higher scores reflecting greater severity and effect on life, and lower scores reflecting greater problems for coping with fatigue.13
The Fatigue Visual Analog Scale (VASF) is a unidimensional measure for severity or intensity of fatigue. It usually comprises a 0-10 cm horizontal line with a statement in each extremity. Higher scores represent greater severity or intensity of fatigue.15 Regarding the VASF scale, the researchers assumed that the values below 2 would be considered as clinically irrelevant fatigue.
The vitality subscale of the SF36 questionnaire derives from a formula using 4 subitems ("a", "e", "g" and "i") of the 9th item of the instrument. Its score varies from 0 to 100 and, the lower the score the greater the fatigue.
The Functional Assessment of Chronic Illness Therapy Fatigue Scale (FACIT-F) was developed for measuring fatigue
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Table 1 - Socioeconomic and demographic data of the patients with clinically relevant fatigue (VASf> 2, n =57).
Table 2 - Independent variables scores of the patients with clinically relevant fatigue (VASf >2, n = 57).
Variable Mean (SD) or n (%)
Age 48.35 (±15)
Gender
Male 6 (10.5%)
Female 51 (89.5%)
Ethnics
White 17 (29.82%)
Pardo 32 (56.14%)
Negro 8 (14.04%)
Social class
A (>20 MW) 0 (0%)
B (10-20 MW) 1 (l.75%)
C (4-10 MW) 2 (3.5%)
D (2-4 MW) 10 (17.55%)
E (<2MW) 44 (77.2%)
Years of disease 4.92 (±3.8)
Marital status
Single 10 (17.55%)
Married/common-law 29 (50.87%)
Divorced 9 (15.79%)
Widow 9 (15.79%)
SD, standard deviation; MW, Brazilian minimum wage.16
Variable Mean/medianb SD/25-75%b
BMI 26.53 4.93
Years of disease 4.92 3.8
Morning stiffness (minutes) 15.00b 0.240b
ERS 9.5b 2.59b
CRPa 0.46b 0.01-16.00b
VAS pain 3.83 2.59
VAS patient 3.94 2.33
VAS provider 2.89 2.38
TJC 2.00b 0-28
SJC 0.00b 0-11b
SDAI 13.89 11.27
CDAI 12.89 10.87
HAQ 1.03 0.89
DAS28 2.9 1.41
BMI, Body Mass Index; ERS, Erythrocyte Sedimentation Rate; CRP, C-Reactive Protein; VAS pain, pain Visual Analog Scale; VAS patient, patient global Visual Analog Scale; VAS provider, provider global Visual Analog Scale; TJC, Tender Joint Count; SJC, Swollen Joint Count; SDAI, Simplified Disease Activity Index; CDAI, Clinical Disease Activity Index; HAQ Health Assessment Questionnaire; DAS28, Disease Activity Score with 28-joint counts. a Data collected from 76 patients.
b Values presented in mean ±SD. Median (25-75%) or as specified in the variable.
in oncology patients with anemia. The FACIT-F covers physical fatigue, functional fatigue, emotional fatigue and social consequences of fatigue. It contains 13 items with 5 responses from "Not at all" to "Very much". The items are scored 0-4, summed, multiplied by 13 and divided by the number of items actually answered. The global score ranges from 0 to 52 with higher scores reflecting less fatigue.15
The same researcher performed all fatigue assessments in order to optimize data collection and to clarify doubts about the items of each instrument.
Statistical analysis
Continuous data were expressed as mean and standard deviation, or 25th and 75th percentiles, according to the sample distribution. Categorical variables were recorded as percentages. Multiple bidirectional stepwise regression was applied due to the large number of potential explanatory variables and the lack of a defined theory to support a specific model of analysis. The analysis considered each fatigue score as dependent variable, and all the others collected as independent variables. The stepwise regression model was used to identify the highest R2 for the tested model. Multicollinearity was considered present in the occurrence of tolerance p <0.1 and VIF close to 1. For the multiple linear regression the assumptions of residues with normal behavior in the graphical representation Q-QPlot and in the Shapiro-Wilk test were met. Statistical significance was set at 5% and all analyses were performed with SAS 9.3 software (SAS Institute Inc., North Carolina, USA).
Results
A total of 80 patients were assessed during the study, and 57 reported clinically relevant fatigue (VASf >2), which represents a point prevalence of 71.25% (51 women [89.5%], mean
Table 3 - Scores of the Fatigue Questionnaires used to assess fatigue in Brazilian RA Cohort patients.
Questionnaire Mean SD
SF36 vitality scale 55.93 ±24.96
VAS fatigue 4.30 ±2.95
POMS fatigue scale 7.95 ±6.28
MAF-GFI 22.79 ±13.38
FSS 4.11 ±1.63
BRAF-MDQ 22.28 ±16.33
BRAF-NRS fatigue 4.88 ±3.02
FACIT-F 35.09 ±11.01
SF36, Short-form 36; VAS, Visual Analog Scale; POMS, Profile of Mood States; MAF-GFI, Multidimensional Assessment of Fatigue-Global Fatigue Index; FSS, Fatigue Severity Scale; BRAF-MDQ, Bristol Rheumatoid Arthritis Fatigue Multi-Dimensional Questionnaire; BRAF-NRS, Bristol Rheumatoid Arthritis Fatigue Numeric Rating Scale; FACIT-F, Functional Assessment of Chronic Illness Therapy Fatigue Scale.
age 48.35 ±15 years, and mean disease duration of 4.92 ±3.8 years). All socioeconomic and demographic data were showed in Table 1.16
SDAI and CDAI scores were 13.89 (11.27) and 12.89 (±10.87), respectively. The participants presented a mean HAQ score of 1.03 (±0.89), mean global pain (VASP) of 3.83 (±2.59) and mean DAS28 of 2.9 (±1.41). All others independent variables values were showed in Table 2. The specific scores of multiple instruments were presented in Table 3.
Regarding the predictive models, the explained variance for all instruments ranged from 21% to 56% (Table 4). The highest coefficient of determination (R2) was 56% for SF-36 and the lowest (R2 = 29%) for BRAF-NRS. All eight predictive models showed statistical significance. In the same way, in
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Table 4 - Correlation analysis of the questionnaires used to assess fatigue in Brazilian RA Cohort patients.
Instrument
R2 adjusted
SF36 vitality scale
VAS fatigue
POMS fatigue scale
MAF-GFI
BRAF-MDQ
BRAF-NRS
FACIT-F
Variable P ß
HAQ 0.000 -0.542
Age 0.001 0.325
Morning 0.003 -0.299
stiffness
Manif. 0.017 -0.217
extra-joint
HAQ 0.000 0.706
VAS pain 0.000 0.697
VAS patient 0.000 0.517
Free T4 0.000 -0.434
Aval. Subj. 0.001 0.370
Cheers
Age 0.007 -0.265
TSH 0.047 -0.188
Age 0.000 -0.501
HAQ 0.002 0.382
Morning 0.036 0.245
stiffness
HAQ 0.000 0.506
Age 0.002 -0.335
Free T4 0.002 -0.349
TSH 0.037 -0.216
Income 0.044 0.217
HAQ 0.000 0.630
Age 0.000 -0.395
HAQ 0.000 0.495
Age 0.001 -0.405
HAQ 0.000 -0.632
Age 0.001 0.354
ESR 0.024 -0.232
BMI 0.032 0.202
HAQ Health Assessment Questionnaire; VAS pain, pain Visual Analog Scale; VAS patient, patient global Visual Analog Scale; TSH, thyroid stimulating hormone; ESR, erythrocyte sedimentation rate; BMI, Body Mass Index.
all prediction models, the total of independent variables also were considered statistically significant. The HAQ was the only independent variable to predict fatigue on all instruments, and the second was age. There was no multicollinearity between the independent variables.
Discussion
This study was the first to assess fatigue in early RA patients, applying all fatigue instruments available in Portuguese, in an attempt to assess with sociodemographic and clinical variables would better predict fatigue.
Early RA affected predominantly women in our study, as expected, and is similar to other Brazilian demographic studies (varyingfrom 86% to 92%).6'17,18 Importantly, women seem to report somewhat more fatigue than men, which could have influenced the high prevalence of fatigue in our study.19 Ethnicity differed (60% mixed race) probably because race was self-reported in our study. At the data collection, patients were
Mental health 64.00
Physical functioning 100.00 62.50
Emotional role functioning
Physical role functioning 25.00
Social role 62.50 functioning
Bodily pain 58.50
General health perceptions
55.00 Vitality
Fig. 1 - SF36 domains scores assessed in the Brazilian RA cohort patients.
asked to choose between the alternatives: black, white, pardo (mixed race), indigene or Asian.
This study identified that fatigue was better predict by disability (assessed with HAQ), independent of the multidimensional instrument, even in patients with low disability. Despite FACIT-F showing a negative value for its results there is a direct correlation with HAQ (the lower the FACIT-F score the higher the fatigue), as observed with the other instruments. This finding agrees with most of the studies analyzed, excluding those studies that did not assess this prediction. The HAQ mean values found in other studies varied from 0.44 to 1.1 also reflecting low disability.6,8,20-30 Thus, it is important to assess fatigue even in patients with little or no functional limitation.
Observing the global assessment of the SF36 questionnaire, presented in Fig. 1, the low median score on the physical aspects assessed by the instrument corroborate with the association with disability found in our study.
Several studies found significant correlation between fatigue and disease activity (DAS28, TJC, SJC, SDAI, CDAI and/or ESR), and most of them assessed patients with moderate to high disease activity.6'8'20'21'23'24 However, the absence disease activity in our study could have occurred because our sample presented disease activity predominantly in remission or low disease activity.
Fatigue is commonly associated with pain, mainly when
assessing fatigue with the VASp8,19,22-24,26,27,29,30 and although
we found mean pain on VASp of 3.99 ± 2.66, which could be considered as mild to moderate pain, these variables showed no prediction.
There were no studies on BRAF-MDQ and BRAF-NRS in early RA to compare with our results.
Interestingly, our study shows that fatigue is also predicted by age - the younger the patient the higher the fatigue perception. This finding might be because the young are more active, performing multiple tasks in personal and professional life. Therefore, this may lead to an important economic and social impact. Nikolaus et al. conducted a qualitative study assessing patients' experience of fatigue and observed that
rev bras reumatol. 2017;xxx(xx):xxx-xxx
younger women with multiple daily roles were more susceptible to fatigue than men and older people.30
Several study limitations impede the generalization of our findings. As it happens in all cross-sectional studies, it is not possible to determine a cause/effect correlation between the variables; and the study of a specific cohort could be a selection bias. Psychosocial variables were not assessed for their correlation, which could affect the results of the study. In the same direction, despite the fact that 40% of the sample presented any comorbidity, it could be interpreted as a confounding variable and thus mediate the relationship between fatigue and disability, or influence the origin of fatigue.
Regarding other variables, such as hypothyroidism and fibromyalgia, the lack of homogeneity of the sample did not allow a significant statistical analysis, thus those were withdrawn as they could be potential confounding variables.
The adoption of different methods of analysis by other authors and the assessment of different variables in each study does not allow a reliable comparison between the available studies. Finally, other studies using different scales were not analyzed.
Longitudinal studies with larger samples could provide stronger evidence about cause/effect correlation between variables and provide a better comprehension on how sensitive to change the instruments actually are, as well as help in selecting the best instruments to assess fatigue.
Fatigue is a prevalent symptom even in early RA patients, thus, it should be considered as an outcome measure due to its impact on patients' lives. However, several simple and multidimensional instruments assess different domains and give different perspectives on how fatigue affects the patients. Identifying the best assessment instrument would result in a better comprehension of the clinical relationships of fatigue.
In conclusion, the prevalence of fatigue was high in early RA using different instruments. We identified that fatigue is better predicted by disability, independent of the multidimensional instrument, and age: the younger the patient the higher the fatigue perception.
Conflicts of interest
The authors declare no conflicts of interest.
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