http://orcid.org/0000-0001-6979-3764
Figures
Abstract
Objective
To describe fatigue in relation to disease-specific and socioeconomic factors and to test possible correlations between fatigue and work impairment, quality of life, pain, sleep, depression, and physical functioning in people with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA).
Methods
A questionnaire-based cross-sectional survey collecting patient characteristics such as disease characteristics, socioeconomic factors and patient-reported outcomes (PROs) from patients with RA, PsA and axSpA in Denmark. PRO scales included the FACIT-Fatigue sub-scale, Work Productivity and Activity Impairment scale (WPAI), EuroQol (EQ-5D), Medical Outcomes Study Sleep Scale (MOS), Major Depression Inventory (MDI), and Health Assessment Questionnaire (HAQ). Respondents were recruited via routine visits to the outpatient rheumatology clinic; information on diagnosis, treatment and disease activity was collected from medical journals by trained nurses.
Results
487 patients participated in the study. Fatigue was more present in women, experienced patients, and patients who changed medication in the past 12 months, who were unemployed, who had less education, and who had lower household income. There was no statistically significant difference between mean fatigue in the three diagnostic groups (p = 0.08). Fatigue correlated with all included PROs (Pearson correlation coefficients, p<0.0001). Stratifying for diagnosis and adjusting for socioeconomic factors did not change the conclusion.
Conclusion
In a stable, representative group of patients with RA, PsA and axSpA, we found significant correlations between fatigue and work impairment, quality of life, pain, sleep, depression and physical functioning. Fatigue cannot be perceived as a single problem, but rather as a symptom that affects broadly.
Citation: Esbensen BA, Stallknecht SE, Madsen ME, Hagelund L, Pilgaard T (2020) Correlations of fatigue in Danish patients with rheumatoid arthritis, psoriatic arthritis and spondyloarthritis. PLoS ONE 15(8): e0237117. https://doi.org/10.1371/journal.pone.0237117
Editor: Luca Navarini, Universita Campus Bio-Medico di Roma, ITALY
Received: April 8, 2020; Accepted: July 20, 2020; Published: August 3, 2020
Copyright: © 2020 Esbensen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: This nonpharmacological work was funded by Pfizer Denmark, which is a commercial company. TP is an employee of Pfizer Denmark and LH is a former employee of Pfizer Denmark. Incentive was a paid vendor and is also a commercial company. SES and MEM are employees of Incentive. The funder provided support in the form of salaries for authors TP and LH. The funder also provided consultation fees for authors SES and MEM of Incentive during the conduct of the study and consultation fees outside the submitted work. BAE is an employee of Rigshospitalet and University of Copenhagen and reports a research grant for data collection and personal fees for lead investigator consultancy on the protocol development from the funder during the conduct of the study. In addition, BAE has received other research grants and personal consultancy fees from the funder outside the submitted work. The specific roles of all authors are articulated in the ‘author contributions’ section.
Competing interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: SES and MEM report grants from Pfizer Denmark during the conduct of the study and grants from Pfizer Denmark outside the submitted work. SES and MEM are employees of Incentive, which was a paid vendor of Pfizer Denmark and a commercial company. BAE is an employee of Rigshospitalet and University of Copenhagen and reports personal fees from Pfizer Denmark during the conduct of the study and grants from Pfizer Denmark and personal fees from Pfizer Denmark outside the submitted work. LH is a former employee of Pfizer Denmark and TP is an employee of Pfizer Denmark (www.pfizer.dk) and reports salaries from Pfizer Denmark. There are no patents, products in development, or marketed products associated with this research to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Introduction
In healthy individuals, fatigue can occur temporarily, whereas in people with inflammatory arthritis (IA), fatigue can be persistent despite sufficient daily rest [1] and despite appropriate treatment with DMARDS (disease-modifying anti-rheumatic drugs) [2].
Fatigue is a common and a comprehensive problem for people with IA, and patients are clinically affected by their fatigue [3]. Several studies have reported prevalence of fatigue in rheumatoid arthritis (RA) ranging from 40% to 90% [3–5]. The existing literature on fatigue associated with IA is primarily based on patients with RA, and limited research has been carried out with psoriatic arthritis (PsA) and spondyloarthritis (axSpA) patients. The only study identified is a global study exploring fatigue in 30 different rheumatic diseases, which found that 41–51% of patients with RA, PsA and axSpA reported severe fatigue [6].
Fatigue is considered a multidimensional and complex phenomenon [7, 8] and is found to be associated with pain [9–12], sleep problems [13] and low physical activity [14]. Also, severe fatigue has been found to predict depression, low physical activity and quality of life, and more healthcare utilisation [15, 16]. On the other hand, depression, reduced illness beliefs, psychological distress and low self-efficacy have been found to contribute to fatigue [17, 18]. There is limited literature on the correlation between disease-specific and socioeconomic factors.
Thus, the aim of this study is first to describe fatigue in relation to disease-specific and socioeconomic factors and second to test possible correlations between fatigue and work impairment, quality of life, pain, sleep, depression and physical functioning in people with RA, PsA and axSpA.
Materials and methods
This study was designed as a cross-sectional survey of people with RA, PsA or axSpA using validated self-reported questionnaires and medical journals. A questionnaire was developed, and data was collected using SurveyXact®.
Respondents who were above the age of 18 years and had a confirmed diagnosis of RA, PsA or axSpA were invited to participate in the study. We aimed for a representative sample of the IA population. Data was collected over a six-month period from January to June 2017 via rheumatology routine visits to Rigshospitalet—Glostrup and Frederiksberg. A detailed description of the methods of the study has previously been published [19].
Characteristics such as type of diagnosis, age, gender, treatment (DMARD or biologic), treatment changes and disease activity score (DAS28 for RA and PsA, BASDAI for axSpA and BASFI for PsA and axSpA) were obtained by study nurses from the respondents’ medical journals. All respondents completed a questionnaire, which included questions related to their disease history, type of household, education, employment, and household income as well as seven validated patient-reported outcomes (PROs) described in the following paragraphs.
The study comprised six standardised questionnaires covering fatigue and different outcomes related to fatigue such as work impairment, quality of life, sleep, depression and physical functioning.
The Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-Fatigue) was used to assess fatigue. FACIT-Fatigue is an internationally recognized disease-specific scale validated to measure fatigue in patients with a chronic illness [20]. Items in the FACIT-Fatigue scale are scored 0–4, and the total FACIT-Fatigue score range is 0–52. The higher the score, the lower the level of fatigue. Work impairment was measured by The Work Productivity and Activity Impairment—Specific Health Problem (WPAI-SHP) scale, a generic scale measuring work productivity and impairment in patients with specific health problems [21]. The WPAI-SHP score provides a percentage from 0% to 100% reflecting level of impairment. Quality of Life was measured with EQ-5D-5L, a generic instrument measuring health-related quality of life from 0 to 1, where 1 is perfect health [22]. Sleep was measured with The Medical Outcomes Study (MOS) sleep scale [23] on a scale of 0 to 100, where 100 indicates severe sleep problems. The Major Depression Inventory (MDI) scale was used to measure mental well-being or depression on a scale from 0 to 50, where <20 is normal and >29 is major depression (32). Physical functioning was measured by The Health Assessment Questionnaire (HAQ) [24]. HAQ assesses physical functioning as difficulty with activities of daily living over the past week, and the score ranges from 0.0 to 3.0. The HAQ-MD score used in this study is the modified DANBIO version in Danish. Pain was measured by a single visual analogue scale (VAS) item from the HAQ questionnaire [25]. Patients were asked “How much pain have you had in the past week?” The scale ranged from 0 to 100.
Statistical analyses
Initially, we presented characteristics of the study population and tested variations in mean-fatigue scores between disease-specific groups and socioeconomic factors applying ANOVA. Subsequently, we assessed correlations by estimating Pearson correlation coefficients between fatigue and the six PROs: work impairment, quality of life, sleep problems, depression, physical functioning and pain. A Pearson correlation coefficient of more than 0.80 or less than -0.80 indicates a strong correlation. A coefficient of 0.40 to 0.80 or -0.40 to -0.80 indicates a moderate correlation. Finally, a coefficient below 0.40 or above -0.40 indicates a weak correlation [26]. Not all respondents answered all items, so the number of respondents varies among the different PROs.
Significant correlations were assessed in linear regressions to test the associations in more detail. Linear regression analyses were applied to estimate the association between fatigue and the six other PROs. The analyses were conducted separately. Thus, we examined the association between fatigue and the six outcomes in separate regressions. The statistical significance level was set at p<0.05.
In these analyses, we estimated the raw associations between fatigue and the PROs and conducted multiple linear regressions adjusted for the following potential confounders: type of disease (RA, PsA, axSpA), gender, age (years), years since diagnosis (0–5, 6–10, 11–15, 16–20, more than 20), treatment change in the past 12 months (0, 1, 2 or more), and current treatment (bsDMARD; csDMARD; bsDMARD and csDMARD; no current treatment). Potential confounders were selected a priori. The raw associations between fatigue and the PROs are illustrated by scatter plots with fit lines (S1 Fig). We used stepwise backward selection to assess whether the associations were best described as linear, quadratic or cubic trends. In addition, we stratified the linear regressions by type of disease to examine whether the associations between fatigue and the PROs differed according to type of disease.
In sensitivity analyses, we assessed whether confounding by socioeconomic factors could have biased our results. Thus, in addition to the remaining confounders, we included the following variables: highest obtained education, type of household (married, single, etc.), employment status (employed, unemployed, retired, etc.) and total household income.
Data management and statistical analyses were conducted using SAS® statistical software version 9.4 and Microsoft Excel®. Analyses followed the STROBE Statement Checklist for cross-sectional studies [27].
The study was conducted under approval of the Danish Data Protection Agency (j.nr. 2012-41-1199) and with approval from the Ethics Committee of the Capital Region of Denmark (Protocol 17021125). The Danish Medicines Agency was informed about the execution of the study, as per current Danish guidelines (case no. 2017071026). All respondents gave their written informed consent before study inclusion.
Results
The study population comprised 487 patients– 292 patients with RA (60%), 85 patients with PsA (17%) and 110 patients with axSpA (23%). The mean score of fatigue was 34.4, see Table 1. Fatigue was present in all three diagnostic groups (RA: 34.9; PsA: 31.8; axSpA: 34.8); albeit, it did not differ significantly between the disease groups (p = 0.08). The majority of the total study population was women (62%), and the mean age was 53.4. Gender, age and medical treatment were significantly correlated with fatigue with women, experienced patients and patients who changed medication in the past 12 months, with all reporting a higher mean fatigue rate. On the other hand, type of IA, age and current treatment had no impact on mean fatigue.
Table 2 presents the socioeconomic characteristics of the population. We found no significant difference of fatigue according to type of household. However, education, employment and income were significantly correlated with fatigue among patients who had less education, were unemployed/retired and had lower income. Those groups showed a higher mean fatigue rate.
Fig 1 presents the Pearson correlation coefficients between fatigue and work impairment, quality of life, sleep, depression, physical functioning and pain, respectively. All correlations have a p-value of <0.0001.
Table 3 presents raw and adjusted linear regressions between fatigue and work impairment, quality of life, pain, sleep, depression and physical functioning. All six regressions show significant associations. For the adjusted association between fatigue and work impairment, the percentage of overall work impairment decreased by 1.4194% when the fatigue score increased by 1 (i.e. less fatigue). The association between fatigue and quality of life was best described as a quadratic trend. Thus, the association was strongest among patients who were suffering the most from fatigue, and the association decreased slightly when the fatigue score increased (fatigue β-value: 0.0232, fatigue2 β-value: -0.0002). The associations between fatigue and sleep problems and fatigue and depression were also best described as quadratic trends. The association between fatigue and sleep problems was strongest among patients who were suffering the most from fatigue, and the association increased slightly when the fatigue score increased (fatigue β-value: 0.1529, fatigue2 β-value: 0.0067). The association between fatigue and depression was strongest among patients who were suffering the most from fatigue, and the association decreased slightly when the fatigue score increased (fatigue β-value: -0.9560, fatigue2 β-value: 0.0052). The associations between fatigue and physical functioning and fatigue and pain were best described as linear trends. The risk of physical disability decreased by -0.0286 when fatigue increased by 1, and the risk of pain decreased by -1.3835 when fatigue increased by 1.
β-values for associations between fatigue and the six other PROs did not change significantly after additional adjustment for socioeconomic factors (S1 Table). We found statistically significant correlations between fatigue and the six other PROs in both RA, PsA and axSpA patients (S2–S4 Tables). None of the stratified analyses differed markedly from the primary non-stratified analysis presented in Table 3.
Discussion
The study shows that the mean fatigue score was considerably lower (34.4) than previously measured in the general population (44.0) [28], which underlines the severity of the problem in patients with IA. Significantly more women experienced fatigue compared with men, which is aligned with previous research that found women with RA had significantly more fatigue compared with men [29]. The reason for this is unclear, but neurophysiological differences could explain why women may experience more sustained inflammation-related fatigue compared with men [29]. Though it might not be the only explanation, a more nuanced understanding of similarities and differences in men and women is needed.
Previous research have shown that people with RA in remission continue reporting high levels of fatigue even when optimally treated with DMARDs [10, 30, 31]. In addition, a recent meta-analysis suggests that biologic treatments have only small-to-moderate effects on fatigue [32]. However, more recent studies suggest that biological treatments could have a positive impact on fatigue [33–35] and hence no consensus has been reached about the relation between fatigue and anti-inflammatory treatment.
We found a significant higher level of fatigue in the respondents who had treatment changes within the past 12 months. Changes in treatment are based on the patient’s overall condition; that is, both objective parameters and the patient’s subjective feedback. Therefore, the obvious conclusion is that patients who change treatment present with several symptoms such as pain and fatigue.
In the analysis of socioeconomic characteristics, we found a significant higher level of fatigue in respondents with less education, respondents who were unemployed/retired and respondents with a lower household income. Socioeconomic status is a well-known predictor for health outcomes, and consequently a higher mortality rate is seen in populations with low socioeconomic status [36]. Low socioeconomic status is shown to be associated with obesity and unhealthy behaviours such as smoking, heavy alcohol use and physical inactivity [37]. Patients with RA have up to a threefold risk of mortality compared with the general population [38], and a systematic review has shown that low socioeconomic status is associated with an increased risk of mortality and functional disability and risk for developing IA [39]. It is important not only for rheumatologists but for all health professionals to be aware of patients with widespread fatigue and whether patients also have low socioeconomic status, because they are expected to be more vulnerable.
The study also showed a correlation between fatigue and work impairment, quality of life, pain, sleep problems, depression and physical functioning, suggesting a close relationship between the reporting of fatigue and a number of other clinical outcomes. These findings were further supported by raw and adjusted linear regressions where we identified the association between fatigue and work impairment, quality of life, pain, sleep problems, depression and physical functioning, respectively.
Despite recent advances in understanding the role of fatigue in IA, including findings that pain, depression and physical activity may correlate with fatigue in RA [12, 14, 40], fatigue remains a challenge in rheumatology clinical practice. Limited evidence currently exists regarding the possible relationship between fatigue in different IA diseases, socioeconomic factors and other PROs, and to our knowledge this study is one of the first to access these correlations across different disease types.
Another challenge in rheumatology practice is the absence of evidence about association between fatigue and central sensitization which may have a major impact on fatigue. A review from 2007 suggests a similarity between fatigue, fibromyalgia and a central sensitization process [41]. Given an overlap between fatigue in people with inflammatory arthritis and people with fibromyalgia, the central sensitization mechanism could explain the occurrence of fatigue in some patient and the absence in other. Though, this hypothesis still needs to be investigated in future research.
People with IA report fatigue as a key issue that rheumatologists frequently overlook [10, 42], and consequently patients often believe they should accept fatigue as a part of their condition. However, based on the complexity of fatigue as we identified, rheumatologists and other health professionals instead need not only to be aware of the impact of fatigue on the individual patient’s life, but also to focus their care specifically on the relationship of fatigue with other aspects of the patient’s everyday life.
Among clinicians there is an increased recognition of the need to manage fatigue. Some evidence is available and has proven the positive effect of psychosocial interventions and physical activity on managing fatigue in people with RA [43]–e.g. mindfulness [44]; exercise [45–47]; cognitive behavioural therapy and self-management [7, 48]–and various intervention studies with a focus on reducing and/or controlling fatigue are evolving [8, 47, 49–54]. However, these studies have mainly focused on patients with RA and have not necessarily considered fatigue as a multidimensional symptom. Our results suggest this needs to be considered in future planning of interventions.
Strengths of our study include the large overall sample size, including the three diagnostic groups within IA (RA, PsA and axSpA), as well as the data source for the patient characteristics. All data was taken from the respondents’ medical journals and recorded by trained study nurses, which excludes potential recall biases seen in other surveys exclusively based on patient-reported data. The recruitment method has ensured a high response rate, and our study is considered representative of the Danish RA, PsA and axSpA populations.
Some limitations of this study should be recognized. The study cohort is slightly older and consists of more women, despite a good representation in the study cohort of both gender and age groups. The study cohort is limited to two clinics in the Capital Region of Denmark, and consequently the geographical scope is limited. Moreover, people with RA represent the majority of the study population and future research should focus on larger disease-specific populations to further investigate fatigue in people with PsA and axSpA. The nature of a cross-sectional study is that we cannot make conclusions concerning causality. It can generate only hypotheses, which can be further analysed in future studies. In this study, we focused on measuring the severity of fatigue using FACIT-Fatigue and VAS fatigue scores, which measured one aspect of fatigue (unidimensional) and not the multidimensional aspects of fatigue, which can be viewed as a limitation.
Conclusion
Based on our study, there are number of socioeconomic factors that might be relevant to screen for when treating patients with RA, PsA and axSpA. Also, a more nuanced understanding of similarities and differences between men and women may inform future interventions for fatigue in patients with IA. To conclude, in a stable, representative group of patients with IA, we found significant correlations between fatigue and work impairment, quality of life, pain, sleep, depression and physical functioning. Fatigue cannot be seen as a single problem, but rather as a symptom that broadly affects the lives of people with IA.
Supporting information
S1 Fig. Scatterplots with fit-lines for the associations between FACIT-Fatigue and WPAI, EQ-5D, MOS sleep scale, MDI, HAQ and pain from HAQ.
https://doi.org/10.1371/journal.pone.0237117.s001
(TIF)
S1 Table. Adjusted linear regressions for the association between fatigue and work impairment, quality of life, sleep problems, depression, physical functioning and pain, respectively, with additional adjustment for socioeconomic factor.
*Adjusted for type of disease (RA, PsA, axSpA), gender, age (in years), years since diagnosis (0–5, 6–10, 11–15, 16–20, more than 20), treatment change in the past 12 months (0, 1, 2 or more) and current treatment (bsDMARD, csDMARD, bsDMARD and csDMARD, no current treatment) in addition to: highest obtained education (elementary school or high school, Secondary or short cycle tertiary, etc.), type of household (married, living alone, etc.), employment status (employed, unemployed, etc.) and total household income (below 400.000 DKK, 400.000 DKK or more, don’t want to answer). Results from six different linear regressions between fatigue and each of the PROs. Higher scores for FACIT-Fatigue, EQ-5D and MOS sleep scale indicate better health. Lower scores for WPAI, MDI, HAQ and VAS pain from HAQ indicate better health.
https://doi.org/10.1371/journal.pone.0237117.s002
(DOCX)
S2 Table. Raw and adjusted linear regressions for the association between fatigue and work impairment, quality of life, sleep problems, depression, physical functioning and pain, respectively, among patients with RA.
*Adjusted for gender, age (in years), years since diagnosis (0–5, 6–10, 11–15, 16–20, more than 20), treatment change in the past 12 months (0, 1, 2 or more) and current treatment (bsDMARD, csDMARD, bsDMARD and csDMARD, no current treatment). Results from six different linear regressions between FACIT-Fatigue and each of the PROs. Higher scores for FACIT-Fatigue, EQ-5D and MOS sleep scale indicate better health. Lower scores for WPAI, MDI, HAQ and VAS pain from HAQ indicate better health.
https://doi.org/10.1371/journal.pone.0237117.s003
(DOCX)
S3 Table. Raw and adjusted linear regressions for the association between fatigue and work impairment, quality of life, sleep problems, depression, physical functioning and pain, respectively, among patients with PsA.
*Adjusted for gender, age (in years), years since diagnosis (0–5, 6–10, 11–15, 16–20, more than 20), treatment change in the past 12 months (0, 1, 2 or more) and current treatment (bsDMARD, csDMARD, bsDMARD and csDMARD, no current treatment). Results from six different linear regressions between FACIT-Fatigue and each of the PROs. Higher scores for FACIT-Fatigue, EQ-5D and MOS sleep scale indicate better health. Lower scores for WPAI, MDI, HAQ and VAS pain from HAQ indicate better health.
https://doi.org/10.1371/journal.pone.0237117.s004
(DOCX)
S4 Table. Raw and adjusted linear regressions for the association between fatigue and work impairment, quality of life, sleep problems, depression, physical functioning and pain, respectively, among patients with axSpA.
*Adjusted for gender, age (in years), years since diagnosis (0–5, 6–10, 11–15, 16–20, more than 20), treatment change in the past 12 months (0, 1, 2 or more) and current treatment (bsDMARD, csDMARD, bsDMARD and csDMARD, no current treatment). Results from six different linear regressions between FACIT-Fatigue and each of the PROs. Higher scores for FACIT-Fatigue, EQ-5D and MOS sleep scale indicate better health. Lower scores for WPAI, MDI, HAQ and VAS pain from HAQ indicate better health.
https://doi.org/10.1371/journal.pone.0237117.s005
(DOCX)
Acknowledgments
The authors thank the study respondents for contributing essential data. We would also like to acknowledge Bianca Bech, Heidi Schrøder, Irene Tarp Jørgensen, Ane Ludvigsen and Pernille Klein for their valuable contribution in recruiting patients to the survey in the two outpatient clinics.
References
- 1. Davies H, Brophy S, Dennis M, Cooksey R, Irvine E, Siebert S. Patient perspectives of managing fatigue in Ankylosing Spondylitis, and views on potential interventions: a qualitative study. BMC musculoskeletal disorders. 2013;14:163. Epub 2013/05/11. pmid:23659344; PubMed Central PMCID: PMC3668149.
- 2. Katz P. Fatigue in Rheumatoid Arthritis. Current rheumatology reports. 2017;19(5):25. Epub 2017/04/08. pmid:28386762.
- 3. Wolfe F, Hawley DJ, Wilson K. The prevalence and meaning of fatigue in rheumatic disease. The Journal of rheumatology. 1996;23(8):1407–17. Epub 1996/08/01. pmid:8856621.
- 4. van Hoogmoed D, Fransen J, Bleijenberg G, van Riel P. Physical and psychosocial correlates of severe fatigue in rheumatoid arthritis. Rheumatology (Oxford, England). 2010;49(7):1294–302. Epub 2010/04/01. pmid:20353956.
- 5. Rupp I, Boshuizen HC, Jacobi CE, Dinant HJ, GA vdB. Impact of fatigue on health-related quality of life in rheumatoid arthritis. Arthritis and rheumatism. 2004;51(4):578–85. pmid:15334430
- 6. Overman CL, Kool MB, Da Silva JA, Geenen R. The prevalence of severe fatigue in rheumatic diseases: an international study. Clinical rheumatology. 2016;35(2):409–15. Epub 2015/08/15. pmid:26272057; PubMed Central PMCID: PMC4752960.
- 7. Hewlett S, Chalder T, Choy E, Cramp F, Davis B, Dures E, et al. Fatigue in rheumatoid arthritis: time for a conceptual model. Rheumatology (Oxford, England). 2011;50(6):1004–6. Epub 2010/09/08. pmid:20819797.
- 8. Hewlett S, Ambler N, Almeida C, Cliss A, Hammond A, Kitchen K, et al. Self-management of fatigue in rheumatoid arthritis: a randomised controlled trial of group cognitive-behavioural therapy. Annals of the rheumatic diseases. 2011;70(6):1060–7. Epub 2011/05/05. pmid:21540202; PubMed Central PMCID: PMC3086034.
- 9. van Dartel SA, Repping-Wuts JW, van Hoogmoed D, Bleijenberg G, van Riel PL, Fransen J. Association between fatigue and pain in rheumatoid arthritis: does pain precede fatigue or does fatigue precede pain? Arthritis care & research. 2013;65(6):862–9. Epub 2013/06/05. pmid:23729241.
- 10. Madsen SG, Danneskiold-Samsoe B, Stockmarr A, Bartels EM. Correlations between fatigue and disease duration, disease activity, and pain in patients with rheumatoid arthritis: a systematic review. Scandinavian journal of rheumatology. 2016;45(4):255–61. Epub 2015/12/23. pmid:26690505.
- 11. Nikolaus S, Bode C, Taal E, van de Laar MA. Fatigue and factors related to fatigue in rheumatoid arthritis: a systematic review. Arthritis care & research. 2013;65(7):1128–46. Epub 2013/01/22. pmid:23335492.
- 12. Katz P, Margaretten M, Trupin L, Schmajuk G, Yazdany J, Yelin E. Role of Sleep Disturbance, Depression, Obesity, and Physical Inactivity in Fatigue in Rheumatoid Arthritis. Arthritis care & research. 2016;68(1):81–90. Epub 2015/03/18. pmid:25779719; PubMed Central PMCID: PMC6083443.
- 13. Loppenthin K, Esbensen BA, Jennum P, Ostergaard M, Tolver A, Thomsen T, et al. Sleep quality and correlates of poor sleep in patients with rheumatoid arthritis. Clinical rheumatology. 2015;34(12):2029–39. Epub 2015/01/27. pmid:25620673.
- 14. Loppenthin K, Esbensen BA, Ostergaard M, Jennum P, Tolver A, Aadahl M, et al. Physical activity and the association with fatigue and sleep in Danish patients with rheumatoid arthritis. Rheumatology international. 2015;35(10):1655–64. Epub 2015/05/08. pmid:25947325.
- 15. Feldthusen C, Bjork M, Forsblad-d'Elia H, Mannerkorpi K. Perception, consequences, communication, and strategies for handling fatigue in persons with rheumatoid arthritis of working age—a focus group study. Clinical rheumatology. 2013;32(5):557–66. Epub 2013/01/08. pmid:23292480.
- 16. Pollard LC, Choy EH, Gonzalez J, Khoshaba B, Scott DL. Fatigue in rheumatoid arthritis reflects pain, not disease activity. Rheumatology (Oxford, England). 2006;45(7):885–9. Epub 2006/02/02. pmid:16449363.
- 17. Matcham F, Ali S, Hotopf M, Chalder T. Psychological correlates of fatigue in rheumatoid arthritis: a systematic review. Clinical psychology review. 2015;39:16–29. Epub 2015/04/29. pmid:25912978.
- 18. Primdahl J, Hegelund A, Lorenzen AG, Loeppenthin K, Dures E, Appel Esbensen B. The Experience of people with rheumatoid arthritis living with fatigue: a qualitative metasynthesis. BMJ Open. 2019;9(3):e024338. Epub 2019/03/23. pmid:30898808; PubMed Central PMCID: PMC6475175.
- 19. Pilgaard T, Hagelund L, Stallknecht SE, Jensen HH, Esbensen BA. Severity of fatigue in people with rheumatoid arthritis, psoriatic arthritis and spondyloarthritis—Results of a cross-sectional study. PloS one. 2019;14(6):e0218831. Epub 2019/06/30. pmid:31251785; PubMed Central PMCID: PMC6599141 following competing interests: SES and HHJ report consultation fees from Pfizer Denmark during the conduct of the study and consultation fees from Pfizer Denmark outside the submitted work. SES and HHJ are employees of Incentive, which was a paid vendor of Pfizer Denmark and a commercial company. BAE is an employee of Rigshospitalet and University of Copenhagen and reports research grant for data collection and personal fees for lead investigator consultancy on the protocol development from the funder during the conduct of the study. In addition, BAE has received research grants and personal consultancy fees from the funder outside the submitted work. TP and LH are employees of Pfizer Denmark and reports salaries from Pfizer Denmark. There are no patents, products in development, or marketed products associated with this research to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
- 20. Webster K, Cella D, Yost K. The Functional Assessment of Chronic Illness Therapy (FACIT) Measurement System: properties, applications, and interpretation. Health and quality of life outcomes. 2003;1:79. Epub 2003/12/18. pmid:14678568; PubMed Central PMCID: PMC317391.
- 21. Zhang W, Bansback N, Boonen A, Young A, Singh A, Anis AH. Validity of the work productivity and activity impairment questionnaire—general health version in patients with rheumatoid arthritis. Arthritis research & therapy. 2010;12(5):R177. Epub 2010/09/24. pmid:20860837; PubMed Central PMCID: PMC2991008.
- 22. Devlin NJ, Shah KK, Feng Y, Mulhern B, van Hout B. Valuing health-related quality of life: An EQ-5D-5L value set for England. Health economics. 2018;27(1):7–22. Epub 2017/08/24. pmid:28833869; PubMed Central PMCID: PMC6680214.
- 23. Wells GA, Li T, Kirwan JR, Peterson J, Aletaha D, Boers M, et al. Assessing quality of sleep in patients with rheumatoid arthritis. The Journal of rheumatology. 2009;36(9):2077–86. Epub 2009/09/10. pmid:19738217.
- 24. Maska L, Anderson J, Michaud K. Measures of functional status and quality of life in rheumatoid arthritis: Health Assessment Questionnaire Disability Index (HAQ), Modified Health Assessment Questionnaire (MHAQ), Multidimensional Health Assessment Questionnaire (MDHAQ), Health Assessment Questionnaire II (HAQ-II), Improved Health Assessment Questionnaire (Improved HAQ), and Rheumatoid Arthritis Quality of Life (RAQoL). Arthritis care & research. 2011;63 Suppl 11:S4–13. Epub 2012/05/25. pmid:22588760.
- 25. Bruce B, Fries JF. The Stanford Health Assessment Questionnaire: dimensions and practical applications. Health and quality of life outcomes. 2003;1:20. Epub 2003/07/02. pmid:12831398; PubMed Central PMCID: PMC165587.
- 26. Schober P, Boer C, Schwarte LA. Correlation Coefficients: Appropriate Use and Interpretation. Anesthesia and analgesia. 2018;126(5):1763–8. Epub 2018/02/27. pmid:29481436.
- 27.
https://www.strobe-statement.org/fileadmin/Strobe/uploads/checklists/STROBE_checklist_v4_combined.pdf.
- 28. Hewlett S, Dures E, Almeida C. Measures of fatigue: Bristol Rheumatoid Arthritis Fatigue Multi-Dimensional Questionnaire (BRAF MDQ), Bristol Rheumatoid Arthritis Fatigue Numerical Rating Scales (BRAF NRS) for severity, effect, and coping, Chalder Fatigue Questionnaire (CFQ), Checklist Individual Strength (CIS20R and CIS8R), Fatigue Severity Scale (FSS), Functional Assessment Chronic Illness Therapy (Fatigue) (FACIT-F), Multi-Dimensional Assessment of Fatigue (MAF), Multi-Dimensional Fatigue Inventory (MFI), Pediatric Quality Of Life (PedsQL) Multi-Dimensional Fatigue Scale, Profile of Fatigue (ProF), Short Form 36 Vitality Subscale (SF-36 VT), and Visual Analog Scales (VAS). Arthritis care & research. 2011;63 Suppl 11:S263–86. Epub 2012/05/25. pmid:22588750.
- 29. Davis MC, Okun MA, Kruszewski D, Zautra AJ, Tennen H. Sex differences in the relations of positive and negative daily events and fatigue in adults with rheumatoid arthritis. The journal of pain: official journal of the American Pain Society. 2010;11(12):1338–47. Epub 2010/05/11. pmid:20452290; PubMed Central PMCID: PMC2920371.
- 30. Druce KL, Bhattacharya Y, Jones GT, Macfarlane GJ, Basu N. Most patients who reach disease remission following anti-TNF therapy continue to report fatigue: results from the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis. Rheumatology (Oxford, England). 2016;55(10):1786–90. Epub 2016/06/23. pmid:27330158.
- 31. Olsen CL, Lie E, Kvien TK, Zangi HA. Predictors of Fatigue in Rheumatoid Arthritis Patients in Remission or in a Low Disease Activity State. Arthritis care & research. 2016;68(7):1043–8. Epub 2015/11/12. pmid:26555897.
- 32. Chauffier K, Salliot C, Berenbaum F, Sellam J. Effect of biotherapies on fatigue in rheumatoid arthritis: a systematic review of the literature and meta-analysis. Rheumatology (Oxford, England). 2012;51(1):60–8. Epub 2011/04/26. pmid:21515629.
- 33. Strand V, Kremer JM, Gruben D, Krishnaswami S, Zwillich SH, Wallenstein GV. Tofacitinib in Combination With Conventional Disease-Modifying Antirheumatic Drugs in Patients With Active Rheumatoid Arthritis: Patient-Reported Outcomes From a Phase III Randomized Controlled Trial. Arthritis care & research. 2017;69(4):592–8. Epub 2016/08/27. pmid:27565000; PubMed Central PMCID: PMC5413813.
- 34. Burmester GR, Feist E, Kellner H, Braun J, Iking-Konert C, Rubbert-Roth A. Effectiveness and safety of the interleukin 6-receptor antagonist tocilizumab after 4 and 24 weeks in patients with active rheumatoid arthritis: the first phase IIIb real-life study (TAMARA). Annals of the rheumatic diseases. 2011;70(5):755–9. Epub 2010/12/29. pmid:21187298; PubMed Central PMCID: PMC3070275 grant support as well as honoraria as speakers from Roche and Chugai. CI-K is an advisor and received honoraria as a speaker from Roche and Chugai.
- 35. Radovits BJ, Fransen J, Al Shamma S, Eijsbouts AM, van Riel PL, Laan RF. Excess mortality emerges after 10 years in an inception cohort of early rheumatoid arthritis. Arthritis care & research. 2010;62(3):362–70. Epub 2010/04/15. pmid:20391482.
- 36. Mackenbach JP, Howden-Chapman P. New perspectives on socioeconomic inequalities in health. Perspectives in biology and medicine. 2003;46(3):428–44. Epub 2003/07/25. pmid:12878812.
- 37. Shin A, Shin S, Kim JH, Ha YJ, Lee YJ, Song YW, et al. Association between socioeconomic status and comorbidities among patients with rheumatoid arthritis: results of a nationwide cross-sectional survey. Rheumatology (Oxford, England). 2019;58(9):1617–22. Epub 2019/03/21. pmid:30892622.
- 38. Lindhardsen J, Ahlehoff O, Gislason GH, Madsen OR, Olesen JB, Torp-Pedersen C, et al. The risk of myocardial infarction in rheumatoid arthritis and diabetes mellitus: a Danish nationwide cohort study. Annals of the rheumatic diseases. 2011;70(6):929–34. Epub 2011/03/11. pmid:21389043.
- 39. Calixto OJ, Anaya JM. Socioeconomic status. The relationship with health and autoimmune diseases. Autoimmunity reviews. 2014;13(6):641–54. Epub 2014/01/15. pmid:24418307.
- 40. Madsen M, Jensen KV, Esbensen BA. Men's experiences of living with ankylosing spondylitis: a qualitative study. Musculoskeletal care. 2015;13(1):31–41. Epub 2014/10/04. pmid:25279843.
- 41. Meeus M, Nijs J. Central sensitization: a biopsychosocial explanation for chronic widespread pain in patients with fibromyalgia and chronic fatigue syndrome. Clinical rheumatology. 2007;26(4):465–73. Epub 2006/11/23. pmid:17115100; PubMed Central PMCID: PMC1820749.
- 42. Repping-Wuts H, Uitterhoeve R, van Riel P, van Achterberg T. Fatigue as experienced by patients with rheumatoid arthritis (RA): a qualitative study. International journal of nursing studies. 2008;45(7):995–1002. Epub 2007/07/31. pmid:17662291.
- 43. Cramp F, Hewlett S, Almeida C, Kirwan JR, Choy EH, Chalder T, et al. Non-pharmacological interventions for fatigue in rheumatoid arthritis. The Cochrane database of systematic reviews. 2013;(8):Cd008322. Epub 2013/08/27. pmid:23975674.
- 44. Zangi HA, Mowinckel P, Finset A, Eriksson LR, Hoystad TO, Lunde AK, et al. A mindfulness-based group intervention to reduce psychological distress and fatigue in patients with inflammatory rheumatic joint diseases: a randomised controlled trial. Annals of the rheumatic diseases. 2012;71(6):911–7. Epub 2011/12/22. pmid:22186709.
- 45. Thomsen T, Aadahl M, Beyer N, Hetland ML, Loppenthin K, Midtgaard J, et al. The efficacy of motivational counselling and SMS reminders on daily sitting time in patients with rheumatoid arthritis: a randomised controlled trial. Annals of the rheumatic diseases. 2017;76(9):1603–6. Epub 2017/06/07. pmid:28584189; PubMed Central PMCID: PMC5561370.
- 46. Thomsen T, Aadahl M, Beyer N, Hetland ML, Loppenthin KB, Midtgaard J, et al. Sustained long-term efficacy of motivational counselling and text message reminders on daily sitting time in patients with rheumatoid arthritis? Long-term follow-up of a randomized, parallel-group trial. Arthritis care & research. 2019. Epub 2019/09/12. pmid:31507095.
- 47. Loppenthin K, Esbensen BA, Jennum P, Ostergaard M, Christensen JF, Thomsen T, et al. Effect of intermittent aerobic exercise on sleep quality and sleep disturbances in patients with rheumatoid arthritis—design of a randomized controlled trial. BMC musculoskeletal disorders. 2014;15:49. Epub 2014/02/25. pmid:24559487; PubMed Central PMCID: PMC3996065.
- 48. Evers AW, Kraaimaat FW, van Riel PL, de Jong AJ. Tailored cognitive-behavioral therapy in early rheumatoid arthritis for patients at risk: a randomized controlled trial. Pain. 2002;100(1–2):141–53. Epub 2002/11/19. pmid:12435467.
- 49. Dures E, Kitchen K, Almeida C, Ambler N, Cliss A, Hammond A, et al. "They didn't tell us, they made us work it out ourselves": patient perspectives of a cognitive-behavioral program for rheumatoid arthritis fatigue. Arthritis care & research. 2012;64(4):494–501. Epub 2011/12/14. pmid:22162339.
- 50. Hewlett S, Ambler N, Almeida C, Blair PS, Choy E, Dures E, et al. Protocol for a randomised controlled trial for Reducing Arthritis Fatigue by clinical Teams (RAFT) using cognitive-behavioural approaches. BMJ Open. 2015;5(8):e009061. Epub 2015/08/08. pmid:26251413; PubMed Central PMCID: PMC4538284.
- 51. Gok Metin Z, Ozdemir L. The Effects of Aromatherapy Massage and Reflexology on Pain and Fatigue in Patients with Rheumatoid Arthritis: A Randomized Controlled Trial. Pain management nursing: official journal of the American Society of Pain Management Nurses. 2016;17(2):140–9. Epub 2016/04/20. pmid:27091583.
- 52. Prioreschi A, Makda MA, Tikly M, McVeigh JA. In Patients with Established RA, Positive Effects of a Randomised Three Month WBV Therapy Intervention on Functional Ability, Bone Mineral Density and Fatigue Are Sustained for up to Six Months. PloS one. 2016;11(4):e0153470. Epub 2016/04/14. pmid:27073832; PubMed Central PMCID: PMC4830593.
- 53. Feldthusen C, Dean E, Forsblad-d'Elia H, Mannerkorpi K. Effects of Person-Centered Physical Therapy on Fatigue-Related Variables in Persons With Rheumatoid Arthritis: A Randomized Controlled Trial. Archives of physical medicine and rehabilitation. 2016;97(1):26–36. Epub 2015/10/21. pmid:26482574.
- 54. Durcan L, Wilson F, Cunnane G. The effect of exercise on sleep and fatigue in rheumatoid arthritis: a randomized controlled study. The Journal of rheumatology. 2014;41(10):1966–73. Epub 2014/08/17. pmid:25128510.