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Fatigue in Ankylosing Spondylitis: Treatment Should Focus on Pain Management
SPONDYLOARTHROPATHIES
Fatigue in Ankylosing Spondylitis: Treatment Should Focus on Pain Management Sinead Brophy, PhD, FRCPH,* Helen Davies, PhD,* Michael S. Dennis, MBBCh, MD, MRCPsych,* Roxanne Cooksey, MSc,* Muhammad J. Husain, PhD,† Elizabeth Irvine,* and Stefan Siebert, MBBCh, MRCP, PhD*
Objectives: Fatigue is an important symptom associated with ankylosing spondylitis (AS). This study examines patients’ perspectives and clinical associations of fatigue to help inform potential strategies to alleviate fatigue in AS. Methods: A mixed methods approach was taken to examine fatigue in a cohort of people with AS. Fatigue levels were evaluated from 3 consecutive monthly questionnaires. Open-ended questions on fatigue were analyzed using thematic analysis and logistic regression was used to examine quantitative data. In addition, fatigue levels were examined before and after treatment with anti-tumor necrosis factor (TNF) compared to nontreated controls. Results: Three hundred forty-eight of 385 participants completed a fatigue questionnaire. Fatigue was reported to have significant physical, social, and psychological effects. A third of the participants reported that there was nothing they could do to reduce their fatigue, whereas other participants reported that medication, exercise, and resting helped. The main factor associated with fatigue was pain [-coefficient: 0.74 (95% CI: 0.66 to 0.81)], whereas depression was much less strongly associated. However, these factors only explained 40% of the variation in fatigue levels. Starting anti-TNF therapy reduced fatigue and pain levels compared to the period of time before taking anti-TNF [difference: 14.4 (95% CI: 5.3 to 23.5) on a scale of 0-100] and this reduction was not seen in controls over the same period. Conclusions: Fatigue is not strongly associated with anxiety, motivation, and depression; instead the factor most associated with fatigue is pain. This suggests that in addition to treatments to reduce disease activity, strategies for alleviating fatigue in AS should focus on pain management techniques and actively treating inflammation. © 2013 Elsevier Inc. All rights reserved. Semin Arthritis Rheum 42:361-367 Keywords: ankylosing spondylitis, epidemiology, disease activity, fatigue, pain
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atigue can be described as an overwhelming sense of tiredness, lack of energy, and feeling of exhaustion (1,2). It affects people in poor and good health and is a multidetermined phenomenon, which is a common feature of a wide variety of conditions such as chronic inflammation, infection, cancer, and mental health disor-
*College of Medicine, Swansea University, Swansea, South Wales, United Kingdom. †Keele Management School, Keele University, Keele, United Kingdom. The work was supported by a Medical Research Council and the National Institute for Social Care and Health Research Patient Research Cohort Initiative grant. The authors have no conflicts of interest to disclose. Address reprint requests to Sinead Brophy, PhD, FRCPH, College of Medicine, Swansea University, South Wales, UK SA2 8PP. E-mail: [email protected].
0049-0172/13/$-see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.semarthrit.2012.06.002
ders (3). In healthy individuals fatigue is a normal experience and temporary, whereas in disease it is chronic or associated with functional impairment of longer duration and is unrelieved by rest and sleep (4-6). Although fatigue associated with rheumatoid arthritis (RA) has long been recognized as an issue requiring attention (7), fatigue associated with ankylosing spondylitis (AS) has been largely overlooked (8). Studies have now demonstrated that over half of the people with AS experience the debilitating phenomenon (8-13), with fatigue now included as a core symptom of the condition (14). There is however no specific agreed treatment for fatigue associated with AS. 361
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Fatigue experienced by people with AS has been shown to be associated with increased disease activity (2,10, 15-18), poorer functional ability (2,10,17,18), pain (10,17,19), stiffness (2,10,17), poorer mental health (1517), such as depression (16), lower global well-being (2,17), impaired work (17), and enthesitis (2). Understandably, an additional factor associated with AS-related fatigue is sleep. Studies report that more than half of the individuals with AS have sleep disorders (11,16,19). The aim of this study was to explore where interventions to address fatigue in AS should be targeted. We have used a mixed methods approach to examine both the patients’ perspectives and the clinical factors associated with fatigue. MATERIALS AND METHODS Participants were people with AS, residing in Wales, UK, who were recruited into an AS cohort via their rheumatologist, general practitioner, or local AS patient support groups. The protocol for the development of the cohort has been published previously (20). Briefly, 572 patients were recruited between 2008 and 2011 and were sent questionnaires every 3 months. Questionnaire Questionnaires examine disease activity (including pain and fatigue), function, medication, and quality of life. Respondents are asked specific questions about flares, exercise, work, health care costs, and coping with AS. Two open-ended questions (essay type) were included in the questionnaire exploring the individual’s experience of fatigue and personal management strategies. The questions were (1) “Please can you describe how fatigue affects you?”, and (2) “Please describe the methods (if any) you have used and how you have found them useful in the management of your fatigue.” In addition, respondents were asked to complete a number of rating instruments measuring fatigue, symptoms of anxiety and depression, exercise activity, motivation, and sleep quality.
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tions relevant to anxiety (7 statements) or depression (7 statements). Each question has 4 possible responses, which are scored on a scale of 0 to 3; the maximum score is 21 for depression and 21 for anxiety, with values of 11 or more on the relevant subscale indicating a probable case. Exercise Activity Exercise was assessed using the International Physical Activity Questionnaire (IPAQ) Short Form (SF) (23). The IPAQ SF is a validated instrument comprising 4 items that can be used to estimate the levels of activity. The IPAQ SF classifies populations into low (scores of ⬍599), moderate (scores between 600 and 2999), or high physical activity level (scores over 3000) groups. Motivation Motivation to exercise was assessed using the Behavioral Regulation in Exercise Questionnaire 2 (BREQ-2) (24), which consists of 19 items measuring the stages of selfdetermination. These items are scored on a 5-point Likert scale. In addition, a unidimensional index of the degree of self-determination known as the relative autonomy index (RAI) (25) is also ascertained from the BREQ-2. Sleep Quality Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) (26), where 9 items related to sleep over the past month are assessed to yield a PSQI score. The range of PSQI scores are 0 (better sleep quality) to 21 (worse sleep quality). Scores of ⱕ5 are associated with better sleep quality and scores of ⬎5 are associated with worse sleep quality. Ethical approval was granted by the London Multicentre Research Ethics Committee and participants gave written consent in accordance to the Declaration of Helsinki. Analysis
Fatigue and Pain
Patients’ Perspective
Fatigue and pain were measured using the single Visual Analog Scale question, which is part of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), “How would you describe the overall level of fatigue/tiredness you have experienced?” (in the past week) and for pain “How would describe the overall level of AS neck, back, or hip pain you have had?” (in the past week). We used the BASDAI measure of fatigue and pain as this is extensively used in clinical practice and allows comparison with other studies in the AS field.
The 2 open-ended questions were examined using a qualitative approach. All responses were imported, read, and coded thematically by 1 researcher (HD) and a second researcher (RC or SB) also coded all responses to validate agreement. Nonagreement was discussed with the third researcher (RC or SB). Each line of the transcript response was individually coded and content was analyzed for emerging themes.
Depression and Anxiety To examine anxiety and depression, we used the Hospital Anxiety and Depression Scale (21,22), which has 14 ques-
Factors Associated with Fatigue Three separate measures of fatigue were collected from questionnaires at baseline, 3, and 6 months’ follow-up. Factor analysis was used to combine all 3 fatigue measures into 1 latent factor global score of fatigue. This method
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Table 1 Demographic Factors
Proportion male (n) Average age (SD) Disease duration (SD) Working (n) Income (for those working) Less than £10,000 £10,000-£29,000 £30,000⫹ Anxiety (SD) Depression (SD) Motivation (SD) Pain (SD) Physical activity (SD) Function (BASFI) (SD) Sleep quality (SD) Diagnosis of inflammatory bowel disease Diagnosis of psoriasis (n) Diagnosis of iritis/uveitis
Low Fatigue (⬍50) (n ⫽ 171)
High Fatigue (⬎50) (n ⫽ 177)
73% (125) 54.2 (13.9) 18.8 (14.7) 54% (92) n ⫽ 96 5% (5) 50% (48) 45% (43) 6.9 (3.4) 5.3 (2.3) 32.0 (23.1) 35.3 (26.1) 3654 (3928) 34.5 (25.4) 1.2 (1.2) 12.9% (22/171)
69% (121) 57.0 (12.6) 19.6 (15.6) 46% (81) n ⫽ 99 17% (17) 57% (56) 26% (26) 9.5 (4.0) 6.8 (2.7) 21.3 (25) 61.4 (25.5) 2534.2 (3405.6) 60.0 (25.8) 1.7 (1.2) 15.2% (27/177)
12% (3.1 to 21.0) 7% (⫺7.3 to 20.1) 18.5% (5.1 to 31.1) ⫺2.6 (⫺3.4 to 1.8) ⫺1.47 (⫺2.0 to ⫺0.9) 10.7 (4.9 to 16.6) ⫺26.1 (⫺31.8 to ⫺20.3) 1119.8 (303.4 to 1936.2) ⫺25.2 (⫺31.2 to ⫺19.8) ⫺0.47 (⫺0.7 to ⫺0.2) 2.4 (⫺5.0 to 9.8)
15.2% (26/171) 42% (71/171)
14.1% (25/177) 42% (74/177)
1.1 (⫺6.4 to 8.6) 0.2 (⫺9.0 to 10.5)
Difference (95% CI) 4.7% (⫺4.8% to 14.5%) ⫺2.8 (⫺5.7 to 0.13) ⫺0.88 (⫺3.5 to 1.7) 8% (⫺2% to 18%)
ensures that temporal fluctuations in fatigue do not influence the data and that the fatigue assessment is not 1 of cross-sectional assessment but is based on 3 longitudinal assessments over a 6-month period. Pain was recorded in the same way at the same 3 time points and combined using factor analysis to give 1 latent pain score. STATA release 13 was used for all analyses. Factors were tested for normality and skewed the medians or proportions if present. Descriptive analysis was used to explore factors associated with fatigue. Regression was performed using step-up selection. All factors associated with high risk from the initial unadjusted analysis were entered into the model and likelihood ratio tests were used to select significant factors for the adjusted model. Goodness-of-fit was assessed using the Hosmer and Lemeshow statistic (27).
Questionnaire
Before and After Compared to Controls
Participants reported that fatigue affected them in 3 main ways: physical, social, and psychological (see supplementary table, available at http://www.semarthritisrheumatism.com). The majority of participants (141/271, 52%) experienced physical symptoms associated with fatigue including tiredness, lack of energy, pain, stiffness, achy limbs/joints, lethargy/restlessness, sleep deprivation, and headaches. Fatigue affected participants socially (87/271, 32%) in that it disrupted and limited basic chores of everyday life such as housework, gardening, or playing with the children. Participants reported tasks taking longer when fatigued. Employment, social, family, and travel plans were disrupted, including work productivity, evenings out with friends, family days out, and holidays, with some participants experiencing worries about driving when fatigued (12/271, 4%). Finally, participants (104/ 271, 38%) reported psychological limitations such as a lack or diminished enthusiasm and motivation, apathy
Matched pair t tests were used to compare fatigue and pain for (1) all participants who were not prescribed antitumor necrosis factor (TNF) at baseline but were prescribed an anti-TNF during follow-up and (2) all participants not prescribed anti-TNF at baseline or at any time during follow-up. This analysis was used to examine the effect of pain/disease activity modification on fatigue levels. RESULTS This analysis looks at the first 6 months of follow-up for the cohort. Of 572 cohort patients, 187 only completed 1 or 2 questionnaires (179 recently recruited, moved, or dropped out and 8 died) and so were not sent a fatigue questionnaire. This meant that 385 people were sent the questionnaire.
The response rate for those sent the fatigue questionnaire was 90% (348/385) with 78% (271/348) and 76% (263/ 348) of patients responding to the open-ended questions relating to the effects and management of fatigue, respectively. The mean level of fatigue was 51.1 (SD: 21.0). Those with higher fatigue scores (⬎50 on a 0-100 scale) reported more pain, anxiety, and depression, and lower income reported poorer sleep quality, less physical activity, and less motivation to exercise than those with low fatigue (⬍50) (Table 1). However, there was no significant difference in gender ratio, age, disease duration, or employment status between these 2 groups. Patients’ Perspective
Model 2 (95% CI)
0.74 (0.66 to 0.045 (0.016 to 0.07)a 0.72 (0.64 to 0.036 (0.003 to 0.067)b
0 (0 to 0) 0.015 (⫺0.006 to 0.36)
at the 95% level.
Of the 348 patients, 344 (98%) had 3 measures of fatigue and pain and could be included in the analysis. Factors associated with fatigue in univariate regression analysis (Table 2) were higher pain, depression, and anxiety scores, worse sleep quality scores, and lower physical activity and motivation scores. The significant variables from the univariate analysis were all included in the same model for a mutually adjusted analysis (where all the variables are adjusted or controlled for each other). In the
aSignificance
Factors Associated with Fatigue
Model 1 (95% CI)
A third (85/263) of the participants who responded to this section of the study reported that nothing helped to manage or reduce their fatigue. Only 5% (14/263) stated that medication helped alleviate fatigue symptoms. The most commonly reported strategy (77/263, 29%) to help manage fatigue symptoms was alternating activity/exercise with periods of rest, sleeping, or “cat napping.” A regular sleeping pattern was reported as being important by only 4% (10/263) of participants. Regular exercise was taken by few, 13% (35/263) of participants, with the most popular activities reported to be walking and swimming, and less popular activities were cycling, yoga, Pilates, and stretching exercises. An optimistic or “work through it” attitude was reported as being helpful in mitigating fatigue by 6/263 (2%) participants (Table 2).
Table 3 Adjusted Analysis for Factors Associated with Fatigue
Management of Fatigue
0.75 (0.67 to 0.03 (⫺0.002 to 0.06) ⫺0.0008 (⫺0.004 to 0.002)
Model 3 (95% CI)
(55/271, 20%), which was exacerbated by low mood (14/ 271, 5%), and depression/anxiety (15/271, 6%). A small number of participants described other emotions: some felt irritable and short-tempered (21/271, 8%), whereas others felt angry and violent (3/271, 1%). Diminished concentration and poor memory or forgetfulness (27/ 271, 10%), feelings of failure, lack of confidence, and a dread of doing things (7/271, 3%) were also associated with fatigue in some people.
0.74 (0.66 to 0.045 (0.016 to 0.07)a
at the 95% level. at the 99% level.
0.82)a
Model 5 (95% CI)
0.12 to 0.31
Pain score Depression Motivation Anxiety Physical activity Sleep quality
bSignificance
Model 4 (95% CI)
aSignificance
⫺0.002 to 0.01 ⫺0.10 to 0.44 0.68 to 0.82 0.08 to 0.16 ⫺0.013 to ⫺0.004 0.06 to 0.11 ⫺0.00008 to ⫺0.00002 ⫺0.31 to 0.32 ⫺0.24 to 0.35
0.8)b
Age 0.0069 Gender 0.16 Pain score 0.75a Depression 0.12a Motivation ⫺0.008a Anxiety 0.087b Physical activity ⫺0.00004b Anti-TNF 0.007 Nonsteroidal 0.58 use Sleep quality 0.21a
0.83)b
B Coefficient 95% Confidence Intervals
0.81)b
Table 2 Unadjusted Analysis for Factors Associated with Fatigue
0.19 (⫺0.04 to 0.84)
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0.74 (0.66 to 0.82)a 0.044 (0.01 to 0.07)b
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Pain 0.74 0.3
Fague
Depression
0.63
0.04 e
Figure 1 Model of factors associated with fatigue.
adjusted multivariate regression (Table 3), the factors associated with fatigue were pain and depression, with a slope of 0.74 indicating that a 1-point rise in pain increases fatigue by 0.74, and a 1-point lowering in depression score would change fatigue by 0.045 (Table 3). This model of pain and depression only explains 40% of the variation in fatigue; thus, 60% of the variation is accounted for by other factors not examined (Fig. 1). Physical activity had no effect on fatigue (when controlled for pain and depression score). Pain and depression were correlated with a 1 SD change in pain associated with a 0.3 SD increase in depression, and conversely, that an increase in depression also increased pain score (Fig. 1). Before and After Compared to Controls To explore the effect of anti-TNF therapy on fatigue, we compared the results of those who started on anti-TNF during follow-up with those who did not receive antiTNF during the follow-up period. The average follow-up time was 8 (range 1 to 24) months. Participants who were prescribed anti-TNF after they started follow-up within the cohort study (n ⫽ 39) had a significant reduction in fatigue [reduction of 14.4 (scale 0 to 100) P ⫽ 0.000 28; Table 4] and pain levels [10.2 (scale 0 to 100) P ⫽ 0.04)] after starting anti-TNF, whereas those never prescribed an anti-TNF within the follow-up period of the cohort (n ⫽ 196) showed no reduction over time in fatigue or
pain. This suggests that anti-TNF did reduce fatigue to non-TNF control levels, but also suggests that significant residual fatigue still remains. Those prescribed anti-TNF were significantly younger (age 49.3 years compared to 55.1 years) [difference 5.8 years (95% CI: 1.86 to 9.7 P ⫽ 0.0039)] but gender ratio was equivalent (21% F:78% M for both) and disease duration (time from first symptoms) was equivalent: non-TNF:TNF, 21.5 years (SD: 15 years): 18.6 years (SD: 13.7 years), respectively [difference: 2.9 years (95% CI: ⫺2.3 to 8.0)]. Stratification by gender suggested that the fatigue was improved for male patients given anti-TNF but less so for female patients. Although the sample size was too small for conclusive results, this suggests that there might be a gender difference in the cause of fatigue in AS. DISCUSSION This study confirms that fatigue is a major symptom of AS, with significant physical, social, and psychological effects. The findings suggest that measures to address fatigue in AS need to focus primarily on the pain rather than anxiety, physical activity, motivation, or sleep. Pain is the single factor examined that contributes most to explaining variation in fatigue. Depression had an effect on fatigue, although the contribution was relatively minor. Additionally, pain was associated with depressive symptoms in this study of AS. The finding that pain rather than sleep deprivation or anxiety is the main determinant of fatigue may explain why many participants felt nothing they did could change their level of fatigue. Although some participants used techniques such as relaxation, trying to have regular sleep and “numbing” the pain/fatigue with drugs such as alcohol, the main feeling was that fatigue was not reduced significantly with lifestyle or behavioral changes. For many patients fatigue was felt to be largely out of their control. Patients who were prescribed an anti-TNF agent showed a reduction in both pain and fatigue, which is also reported in trials of anti-TNF agents in AS (28), there-
Table 4 Before and After Compared to Controls Over Study of Before and After the Prescription of Anti-TNF
Anti-TNF treated (n ⫽ 39) Fatigue Male patients (n ⫽ 29) Female patients (n ⫽ 10) Pain BASDAI Control (n ⫽ 196) Fatigue Male patients (n ⫽ 154) Female patients (n ⫽ 41) Pain BASDAI
Baseline (SD)
Follow-Up (SD)
(No anti-TNF) 66.2 (26) 65.4 (27.4) 68.1 (26.5) 64.7 (24.2) 58.9 (23.7) (No anti-TNF) 46.6 (28.4) 45.4 (28.2) 50.8 (29.5) 45.1 (29.9) 39.2 (24.0)
(Anti-TNF) 51.8 (29) 49.7 (28.5) 61.6 (27.5) 54.4 (28.7) 46.6 (26.2) (No anti-TNF) 44.8 (28.0) 42.1 (27.6) 54.7 (26.6) 45.2 (30.0) 38.7 (23.7)
Difference (95% CI)
Significance P Value
14.4 (5.3 to 23.5) 15.7 (4.2 to 27.3) 6.5 (⫺7.7 to 20.7) 10.2 (0.47 to 20.0) 12.3 (4.2 to 20.3)
0.0028 0.0095 0.3 0.04 0.0039
1.77 (⫺1.6 to 5.2) 3.3 (⫺0.5 to 7.1) ⫺4.0 (⫺11.6 to 3.7) ⫺0.1 (⫺0.3 to 0.1) 0.49 (⫺2.26 to 3.2)
0.3 0.9 0.3 0.3 0.7
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fore, supporting the finding that interventions that target disease activity will alleviate fatigue. It is likely that antiTNF affects the inflammatory pathways that are common to pain and fatigue pathways. The finding that alleviating fatigue needs to focus on targeting pain is supported by findings from other studies. For example, recent work in osteoarthritis (29) found that pain determined depressed mood through its effect on fatigue and disability. This study concluded that there is a need for improved pain management to prevent downstream effects on disability and mood. Pain is the most powerful predictor of fatigue (13,16), and effective disease-modifying therapy, namely, anti-TNF, has been shown to improve sleep (30) and fatigue (31,32). In RA, however, a recent meta-analysis has suggested that the overall effect of biologic therapies on fatigue in RA, although significant, is relatively small (33). This is consistent with our results where, despite an improvement in levels of fatigue and pain, the AS patients on anti-TNF still had significant residual fatigue (mean 51.8 on a scale of 0-100) and pain (mean 54.4 on a scale of 0-100). The anti-TNF improved fatigue by 14% and pain by only 10%, suggesting in this group of patients that although the minimal clinically important difference was reached (34), the majority of the factors causing the disease activity have not been addressed. This is also consistent with the complex causality of fatigue in chronic inflammatory conditions (35), which include “central” fatigue (36,37), which may be unaffected by peripheral immunosuppression. Thus, other pain management strategies may prove beneficial in alleviating fatigue. For example, mindfulness-based stress reduction (MBSR) has been shown to be of benefit in coping with a variety of chronic conditions associated with disability (38). In particular, MBSR was originally introduced into clinical practice as an intervention for chronic pain (39) and the evidence for MBSR improving acceptance of pain and the associated well-being and physical function is growing (40). For example, in multiple sclerosis, where people experience musculoskeletal and neurogenic pain, MBSR has been shown to improve the quality of life with particular benefits for fatigue (41) and there have been calls for assessing nonpharmaceutical treatments such as cognitive behavioral therapy and graded exercise directly on their effect on fatigue in RA, lupus, and fibromyalgia (42). Therefore, perhaps there should also be assessment of these therapies for fatigue in AS. Strengths and Limitations of the Study The response rate for this questionnaire was high (90%) and this may be indicative of the importance fatigue plays in the lives of people with AS. However, it is possible that the patients who dropped out of the cohort may have had different responses to those remaining within the cohort. We do not have an objective assessment of fatigue and rely on a subjective self-report. There are currently no biochemical markers that can be used to assess fatigue levels objectively. Therefore, the 2 main factors studied in this
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study, namely pain and fatigue, are subjective self-reported outcomes. However, we have tried to overcome limitations in day-to-day subjective changes in fatigue and pain levels by taking an average of 3 questionnaires spanning a 6-month period of disease. This study used open-ended questions to give a first impression of qualitative aspects of fatigue. However, interviews and focus groups can offer more detailed exploration that can be given by open-ended questions and we have now performed focus groups within this study and will be publishing these findings separately. The patients prescribed anti-TNF were younger with high disease activity compared to non-TNF patients. Thus, although TNF reduced fatigue in this group, it is possible that in these patients fatigue was more strongly linked to pain/activity and that fatigue in the non-TNF group may have different causal factors. In conclusion, this study finds that fatigue is a major aspect of the disease activity and is strongly associated with pain but that 63% of the variation in fatigue still remains unexplained. Anti-TNF medication does reduce fatigue but residual fatigue and pain still remain. Strategies to alleviate fatigue should focus on interventions that target the pain with perhaps a focus on targeting pain management with therapies such as mindfulness and cognitive behavioral therapy. ACKNOWLEDGMENTS This study was funded by the Medical Research Council (MRC) and the National Institute for Social Care and Health Research (NISCHR). We would like to thank all the people with ankylosing spondylitis who have participated in the study. APPENDIX. SUPPLEMENTARY DATA Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/ 10.1016/j.semarthrit.2012.06.002. REFERENCES 1. Krupp LB, Pollina DA. Mechanisms and management of fatigue in progressive neurological disorders. Curr Opin Neurol 1996; 9(6):456-60. 2. Ibn Yacoub Y, Amine B, Laatiris A, Abouqal R, Hajjaj-Hassouni N. Assessment of fatigue in Moroccan patients with ankylosing spondylitis. Clin Rheumatol 2010;29(11):1295-9. 3. Swain MG. Fatigue in chronic disease. Clin Sci (Lond) 2000; 99(1):1-8. 4. Trendall J. Concept analysis: Chronic fatigue. J Adv Nurs 2000; 32(5):1126-31. 5. Belza B. The impact of fatigue on exercise performance. Arthritis Care Res 1994;7(4):176-80. 6. Repping-Wuts H, Fransen J, van Achterberg T, Bleijenberg G, van Riel P. Persistent severe fatigue in patients with rheumatoid arthritis. J Clin Nurs 2007;16(11C):377-83. 7. Smith RD, Polley HF. Rest therapy for rheumatoid arthritis. Mayo Clin Proc 1978;53(3):141-5.
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367 25. Ryan RM, Connell JP. Perceived locus of causality and internalization: Examining reasons for acting in two domains. J Pers Soc Psychol 1989;57(5):749-61. 26. Buysse DJ, Reynolds CF, 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Res 1989;28(2):193213. 27. Hosmer D, Lemeshow S. Applied logistic regression. 2nd ed. Wiley Interscience; 2000. 28. Calin A, Dijkmans BA, Emery P, Hakala M, Kalden J, LeirisaloRepo M, et al. Outcomes of a multicentre randomised clinical trial of etanercept to treat ankylosing spondylitis. Ann Rheum Dis 2004;63(12):1594-600. 29. Hawker GA, Gignac MA, Badley E, Davis AM, French MR, Li Y, et al. A longitudinal study to explain the pain-depression link in older adults with osteoarthritis. Arthritis Care Res (Hoboken) 2011;63(10):1382-90. 30. Rudwaleit M, Gooch K, Michel B, Herold M, Thörner A, Wong R, et al. Adalimumab improves sleep and sleep quality in patients with active ankylosing spondylitis. J Rheumatol 2011;38(1): 79-86. 31. Revicki DA, Luo MP, Wordsworth P, Wong RL, Chen N, Davis JC, et al. Adalimumab reduces pain, fatigue, and stiffness in patients with ankylosing spondylitis: Results from the adalimumab trial evaluating long-term safety and efficacy for ankylosing spondylitis (ATLAS). J Rheumatol 2008;35(7):1346-53. 32. Missaoui B, Revel M. Fatigue in ankylosing spondylitis. Ann Readapt Med Phys 2006;49(6):305-8, 389-91. 33. 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) 2012; 51(1):60-8. 34. Pavy S, Brophy S, Calin A. Establishment of the minimum clinically important difference for the bath ankylosing spondylitis indices: A prospective study. J Rheumatol 2005;32(1):80-5. 35. 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) 2011;50(6):1004-6. 36. Swain MG. Fatigue in liver disease: Pathophysiology and clinical management. Can J Gastroenterol 2006;20(3):181-8. 37. Davis MP, Walsh D. Mechanisms of fatigue. J Support Oncol 2010;8(4):164-74. 38. Grossman P, Niemann L, Schmidt S, Walach H. Mindfulnessbased stress reduction and health benefits. A meta-analysis. J Psychosom Res 2004;57(1):35-43. 39. Kabat-Zinn J. An outpatient program in behavioral medicine for chronic pain patients based on the practice of mindfulness meditation: Theoretical considerations and preliminary results. Gen Hosp Psychiatry 1982;4(1):33-47. 40. Morone NE, Greco CM, Weiner DK. Mindfulness meditation for the treatment of chronic low back pain in older adults: A randomized controlled pilot study. Pain 2008;134(3):310-9. 41. Grossman P, Kappos L, Gensicke H, D’Souza M, Mohr DC, Penner IK, et al. MS quality of life, depression, and fatigue improve after mindfulness training: A randomized trial. Neurology 2010;75(13):1141-9. 42. Richards S, Westlake S. Fatigue in RA: Looking beyond the formulary. Rheumatol Oxf Engl 2012;51:1-2.
Fatigue in Ankylosing Spondylitis: Treatment Should Focus on Pain Management Sinead Brophy, PhD, FRCPH,* Helen Davies, PhD,* Michael S. Dennis, MBBCh, MD, MRCPsych,* Roxanne Cooksey, MSc,* Muhammad J. Husain, PhD,† Elizabeth Irvine,* and Stefan Siebert, MBBCh, MRCP, PhD*
Objectives: Fatigue is an important symptom associated with ankylosing spondylitis (AS). This study examines patients’ perspectives and clinical associations of fatigue to help inform potential strategies to alleviate fatigue in AS. Methods: A mixed methods approach was taken to examine fatigue in a cohort of people with AS. Fatigue levels were evaluated from 3 consecutive monthly questionnaires. Open-ended questions on fatigue were analyzed using thematic analysis and logistic regression was used to examine quantitative data. In addition, fatigue levels were examined before and after treatment with anti-tumor necrosis factor (TNF) compared to nontreated controls. Results: Three hundred forty-eight of 385 participants completed a fatigue questionnaire. Fatigue was reported to have significant physical, social, and psychological effects. A third of the participants reported that there was nothing they could do to reduce their fatigue, whereas other participants reported that medication, exercise, and resting helped. The main factor associated with fatigue was pain [-coefficient: 0.74 (95% CI: 0.66 to 0.81)], whereas depression was much less strongly associated. However, these factors only explained 40% of the variation in fatigue levels. Starting anti-TNF therapy reduced fatigue and pain levels compared to the period of time before taking anti-TNF [difference: 14.4 (95% CI: 5.3 to 23.5) on a scale of 0-100] and this reduction was not seen in controls over the same period. Conclusions: Fatigue is not strongly associated with anxiety, motivation, and depression; instead the factor most associated with fatigue is pain. This suggests that in addition to treatments to reduce disease activity, strategies for alleviating fatigue in AS should focus on pain management techniques and actively treating inflammation. © 2013 Elsevier Inc. All rights reserved. Semin Arthritis Rheum 42:361-367 Keywords: ankylosing spondylitis, epidemiology, disease activity, fatigue, pain
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atigue can be described as an overwhelming sense of tiredness, lack of energy, and feeling of exhaustion (1,2). It affects people in poor and good health and is a multidetermined phenomenon, which is a common feature of a wide variety of conditions such as chronic inflammation, infection, cancer, and mental health disor-
*College of Medicine, Swansea University, Swansea, South Wales, United Kingdom. †Keele Management School, Keele University, Keele, United Kingdom. The work was supported by a Medical Research Council and the National Institute for Social Care and Health Research Patient Research Cohort Initiative grant. The authors have no conflicts of interest to disclose. Address reprint requests to Sinead Brophy, PhD, FRCPH, College of Medicine, Swansea University, South Wales, UK SA2 8PP. E-mail: [email protected].
0049-0172/13/$-see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.semarthrit.2012.06.002
ders (3). In healthy individuals fatigue is a normal experience and temporary, whereas in disease it is chronic or associated with functional impairment of longer duration and is unrelieved by rest and sleep (4-6). Although fatigue associated with rheumatoid arthritis (RA) has long been recognized as an issue requiring attention (7), fatigue associated with ankylosing spondylitis (AS) has been largely overlooked (8). Studies have now demonstrated that over half of the people with AS experience the debilitating phenomenon (8-13), with fatigue now included as a core symptom of the condition (14). There is however no specific agreed treatment for fatigue associated with AS. 361
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Fatigue experienced by people with AS has been shown to be associated with increased disease activity (2,10, 15-18), poorer functional ability (2,10,17,18), pain (10,17,19), stiffness (2,10,17), poorer mental health (1517), such as depression (16), lower global well-being (2,17), impaired work (17), and enthesitis (2). Understandably, an additional factor associated with AS-related fatigue is sleep. Studies report that more than half of the individuals with AS have sleep disorders (11,16,19). The aim of this study was to explore where interventions to address fatigue in AS should be targeted. We have used a mixed methods approach to examine both the patients’ perspectives and the clinical factors associated with fatigue. MATERIALS AND METHODS Participants were people with AS, residing in Wales, UK, who were recruited into an AS cohort via their rheumatologist, general practitioner, or local AS patient support groups. The protocol for the development of the cohort has been published previously (20). Briefly, 572 patients were recruited between 2008 and 2011 and were sent questionnaires every 3 months. Questionnaire Questionnaires examine disease activity (including pain and fatigue), function, medication, and quality of life. Respondents are asked specific questions about flares, exercise, work, health care costs, and coping with AS. Two open-ended questions (essay type) were included in the questionnaire exploring the individual’s experience of fatigue and personal management strategies. The questions were (1) “Please can you describe how fatigue affects you?”, and (2) “Please describe the methods (if any) you have used and how you have found them useful in the management of your fatigue.” In addition, respondents were asked to complete a number of rating instruments measuring fatigue, symptoms of anxiety and depression, exercise activity, motivation, and sleep quality.
Fatigue in ankylosing spondylitis
tions relevant to anxiety (7 statements) or depression (7 statements). Each question has 4 possible responses, which are scored on a scale of 0 to 3; the maximum score is 21 for depression and 21 for anxiety, with values of 11 or more on the relevant subscale indicating a probable case. Exercise Activity Exercise was assessed using the International Physical Activity Questionnaire (IPAQ) Short Form (SF) (23). The IPAQ SF is a validated instrument comprising 4 items that can be used to estimate the levels of activity. The IPAQ SF classifies populations into low (scores of ⬍599), moderate (scores between 600 and 2999), or high physical activity level (scores over 3000) groups. Motivation Motivation to exercise was assessed using the Behavioral Regulation in Exercise Questionnaire 2 (BREQ-2) (24), which consists of 19 items measuring the stages of selfdetermination. These items are scored on a 5-point Likert scale. In addition, a unidimensional index of the degree of self-determination known as the relative autonomy index (RAI) (25) is also ascertained from the BREQ-2. Sleep Quality Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) (26), where 9 items related to sleep over the past month are assessed to yield a PSQI score. The range of PSQI scores are 0 (better sleep quality) to 21 (worse sleep quality). Scores of ⱕ5 are associated with better sleep quality and scores of ⬎5 are associated with worse sleep quality. Ethical approval was granted by the London Multicentre Research Ethics Committee and participants gave written consent in accordance to the Declaration of Helsinki. Analysis
Fatigue and Pain
Patients’ Perspective
Fatigue and pain were measured using the single Visual Analog Scale question, which is part of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), “How would you describe the overall level of fatigue/tiredness you have experienced?” (in the past week) and for pain “How would describe the overall level of AS neck, back, or hip pain you have had?” (in the past week). We used the BASDAI measure of fatigue and pain as this is extensively used in clinical practice and allows comparison with other studies in the AS field.
The 2 open-ended questions were examined using a qualitative approach. All responses were imported, read, and coded thematically by 1 researcher (HD) and a second researcher (RC or SB) also coded all responses to validate agreement. Nonagreement was discussed with the third researcher (RC or SB). Each line of the transcript response was individually coded and content was analyzed for emerging themes.
Depression and Anxiety To examine anxiety and depression, we used the Hospital Anxiety and Depression Scale (21,22), which has 14 ques-
Factors Associated with Fatigue Three separate measures of fatigue were collected from questionnaires at baseline, 3, and 6 months’ follow-up. Factor analysis was used to combine all 3 fatigue measures into 1 latent factor global score of fatigue. This method
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Table 1 Demographic Factors
Proportion male (n) Average age (SD) Disease duration (SD) Working (n) Income (for those working) Less than £10,000 £10,000-£29,000 £30,000⫹ Anxiety (SD) Depression (SD) Motivation (SD) Pain (SD) Physical activity (SD) Function (BASFI) (SD) Sleep quality (SD) Diagnosis of inflammatory bowel disease Diagnosis of psoriasis (n) Diagnosis of iritis/uveitis
Low Fatigue (⬍50) (n ⫽ 171)
High Fatigue (⬎50) (n ⫽ 177)
73% (125) 54.2 (13.9) 18.8 (14.7) 54% (92) n ⫽ 96 5% (5) 50% (48) 45% (43) 6.9 (3.4) 5.3 (2.3) 32.0 (23.1) 35.3 (26.1) 3654 (3928) 34.5 (25.4) 1.2 (1.2) 12.9% (22/171)
69% (121) 57.0 (12.6) 19.6 (15.6) 46% (81) n ⫽ 99 17% (17) 57% (56) 26% (26) 9.5 (4.0) 6.8 (2.7) 21.3 (25) 61.4 (25.5) 2534.2 (3405.6) 60.0 (25.8) 1.7 (1.2) 15.2% (27/177)
12% (3.1 to 21.0) 7% (⫺7.3 to 20.1) 18.5% (5.1 to 31.1) ⫺2.6 (⫺3.4 to 1.8) ⫺1.47 (⫺2.0 to ⫺0.9) 10.7 (4.9 to 16.6) ⫺26.1 (⫺31.8 to ⫺20.3) 1119.8 (303.4 to 1936.2) ⫺25.2 (⫺31.2 to ⫺19.8) ⫺0.47 (⫺0.7 to ⫺0.2) 2.4 (⫺5.0 to 9.8)
15.2% (26/171) 42% (71/171)
14.1% (25/177) 42% (74/177)
1.1 (⫺6.4 to 8.6) 0.2 (⫺9.0 to 10.5)
Difference (95% CI) 4.7% (⫺4.8% to 14.5%) ⫺2.8 (⫺5.7 to 0.13) ⫺0.88 (⫺3.5 to 1.7) 8% (⫺2% to 18%)
ensures that temporal fluctuations in fatigue do not influence the data and that the fatigue assessment is not 1 of cross-sectional assessment but is based on 3 longitudinal assessments over a 6-month period. Pain was recorded in the same way at the same 3 time points and combined using factor analysis to give 1 latent pain score. STATA release 13 was used for all analyses. Factors were tested for normality and skewed the medians or proportions if present. Descriptive analysis was used to explore factors associated with fatigue. Regression was performed using step-up selection. All factors associated with high risk from the initial unadjusted analysis were entered into the model and likelihood ratio tests were used to select significant factors for the adjusted model. Goodness-of-fit was assessed using the Hosmer and Lemeshow statistic (27).
Questionnaire
Before and After Compared to Controls
Participants reported that fatigue affected them in 3 main ways: physical, social, and psychological (see supplementary table, available at http://www.semarthritisrheumatism.com). The majority of participants (141/271, 52%) experienced physical symptoms associated with fatigue including tiredness, lack of energy, pain, stiffness, achy limbs/joints, lethargy/restlessness, sleep deprivation, and headaches. Fatigue affected participants socially (87/271, 32%) in that it disrupted and limited basic chores of everyday life such as housework, gardening, or playing with the children. Participants reported tasks taking longer when fatigued. Employment, social, family, and travel plans were disrupted, including work productivity, evenings out with friends, family days out, and holidays, with some participants experiencing worries about driving when fatigued (12/271, 4%). Finally, participants (104/ 271, 38%) reported psychological limitations such as a lack or diminished enthusiasm and motivation, apathy
Matched pair t tests were used to compare fatigue and pain for (1) all participants who were not prescribed antitumor necrosis factor (TNF) at baseline but were prescribed an anti-TNF during follow-up and (2) all participants not prescribed anti-TNF at baseline or at any time during follow-up. This analysis was used to examine the effect of pain/disease activity modification on fatigue levels. RESULTS This analysis looks at the first 6 months of follow-up for the cohort. Of 572 cohort patients, 187 only completed 1 or 2 questionnaires (179 recently recruited, moved, or dropped out and 8 died) and so were not sent a fatigue questionnaire. This meant that 385 people were sent the questionnaire.
The response rate for those sent the fatigue questionnaire was 90% (348/385) with 78% (271/348) and 76% (263/ 348) of patients responding to the open-ended questions relating to the effects and management of fatigue, respectively. The mean level of fatigue was 51.1 (SD: 21.0). Those with higher fatigue scores (⬎50 on a 0-100 scale) reported more pain, anxiety, and depression, and lower income reported poorer sleep quality, less physical activity, and less motivation to exercise than those with low fatigue (⬍50) (Table 1). However, there was no significant difference in gender ratio, age, disease duration, or employment status between these 2 groups. Patients’ Perspective
Model 2 (95% CI)
0.74 (0.66 to 0.045 (0.016 to 0.07)a 0.72 (0.64 to 0.036 (0.003 to 0.067)b
0 (0 to 0) 0.015 (⫺0.006 to 0.36)
at the 95% level.
Of the 348 patients, 344 (98%) had 3 measures of fatigue and pain and could be included in the analysis. Factors associated with fatigue in univariate regression analysis (Table 2) were higher pain, depression, and anxiety scores, worse sleep quality scores, and lower physical activity and motivation scores. The significant variables from the univariate analysis were all included in the same model for a mutually adjusted analysis (where all the variables are adjusted or controlled for each other). In the
aSignificance
Factors Associated with Fatigue
Model 1 (95% CI)
A third (85/263) of the participants who responded to this section of the study reported that nothing helped to manage or reduce their fatigue. Only 5% (14/263) stated that medication helped alleviate fatigue symptoms. The most commonly reported strategy (77/263, 29%) to help manage fatigue symptoms was alternating activity/exercise with periods of rest, sleeping, or “cat napping.” A regular sleeping pattern was reported as being important by only 4% (10/263) of participants. Regular exercise was taken by few, 13% (35/263) of participants, with the most popular activities reported to be walking and swimming, and less popular activities were cycling, yoga, Pilates, and stretching exercises. An optimistic or “work through it” attitude was reported as being helpful in mitigating fatigue by 6/263 (2%) participants (Table 2).
Table 3 Adjusted Analysis for Factors Associated with Fatigue
Management of Fatigue
0.75 (0.67 to 0.03 (⫺0.002 to 0.06) ⫺0.0008 (⫺0.004 to 0.002)
Model 3 (95% CI)
(55/271, 20%), which was exacerbated by low mood (14/ 271, 5%), and depression/anxiety (15/271, 6%). A small number of participants described other emotions: some felt irritable and short-tempered (21/271, 8%), whereas others felt angry and violent (3/271, 1%). Diminished concentration and poor memory or forgetfulness (27/ 271, 10%), feelings of failure, lack of confidence, and a dread of doing things (7/271, 3%) were also associated with fatigue in some people.
0.74 (0.66 to 0.045 (0.016 to 0.07)a
at the 95% level. at the 99% level.
0.82)a
Model 5 (95% CI)
0.12 to 0.31
Pain score Depression Motivation Anxiety Physical activity Sleep quality
bSignificance
Model 4 (95% CI)
aSignificance
⫺0.002 to 0.01 ⫺0.10 to 0.44 0.68 to 0.82 0.08 to 0.16 ⫺0.013 to ⫺0.004 0.06 to 0.11 ⫺0.00008 to ⫺0.00002 ⫺0.31 to 0.32 ⫺0.24 to 0.35
0.8)b
Age 0.0069 Gender 0.16 Pain score 0.75a Depression 0.12a Motivation ⫺0.008a Anxiety 0.087b Physical activity ⫺0.00004b Anti-TNF 0.007 Nonsteroidal 0.58 use Sleep quality 0.21a
0.83)b
B Coefficient 95% Confidence Intervals
0.81)b
Table 2 Unadjusted Analysis for Factors Associated with Fatigue
0.19 (⫺0.04 to 0.84)
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0.74 (0.66 to 0.82)a 0.044 (0.01 to 0.07)b
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Pain 0.74 0.3
Fague
Depression
0.63
0.04 e
Figure 1 Model of factors associated with fatigue.
adjusted multivariate regression (Table 3), the factors associated with fatigue were pain and depression, with a slope of 0.74 indicating that a 1-point rise in pain increases fatigue by 0.74, and a 1-point lowering in depression score would change fatigue by 0.045 (Table 3). This model of pain and depression only explains 40% of the variation in fatigue; thus, 60% of the variation is accounted for by other factors not examined (Fig. 1). Physical activity had no effect on fatigue (when controlled for pain and depression score). Pain and depression were correlated with a 1 SD change in pain associated with a 0.3 SD increase in depression, and conversely, that an increase in depression also increased pain score (Fig. 1). Before and After Compared to Controls To explore the effect of anti-TNF therapy on fatigue, we compared the results of those who started on anti-TNF during follow-up with those who did not receive antiTNF during the follow-up period. The average follow-up time was 8 (range 1 to 24) months. Participants who were prescribed anti-TNF after they started follow-up within the cohort study (n ⫽ 39) had a significant reduction in fatigue [reduction of 14.4 (scale 0 to 100) P ⫽ 0.000 28; Table 4] and pain levels [10.2 (scale 0 to 100) P ⫽ 0.04)] after starting anti-TNF, whereas those never prescribed an anti-TNF within the follow-up period of the cohort (n ⫽ 196) showed no reduction over time in fatigue or
pain. This suggests that anti-TNF did reduce fatigue to non-TNF control levels, but also suggests that significant residual fatigue still remains. Those prescribed anti-TNF were significantly younger (age 49.3 years compared to 55.1 years) [difference 5.8 years (95% CI: 1.86 to 9.7 P ⫽ 0.0039)] but gender ratio was equivalent (21% F:78% M for both) and disease duration (time from first symptoms) was equivalent: non-TNF:TNF, 21.5 years (SD: 15 years): 18.6 years (SD: 13.7 years), respectively [difference: 2.9 years (95% CI: ⫺2.3 to 8.0)]. Stratification by gender suggested that the fatigue was improved for male patients given anti-TNF but less so for female patients. Although the sample size was too small for conclusive results, this suggests that there might be a gender difference in the cause of fatigue in AS. DISCUSSION This study confirms that fatigue is a major symptom of AS, with significant physical, social, and psychological effects. The findings suggest that measures to address fatigue in AS need to focus primarily on the pain rather than anxiety, physical activity, motivation, or sleep. Pain is the single factor examined that contributes most to explaining variation in fatigue. Depression had an effect on fatigue, although the contribution was relatively minor. Additionally, pain was associated with depressive symptoms in this study of AS. The finding that pain rather than sleep deprivation or anxiety is the main determinant of fatigue may explain why many participants felt nothing they did could change their level of fatigue. Although some participants used techniques such as relaxation, trying to have regular sleep and “numbing” the pain/fatigue with drugs such as alcohol, the main feeling was that fatigue was not reduced significantly with lifestyle or behavioral changes. For many patients fatigue was felt to be largely out of their control. Patients who were prescribed an anti-TNF agent showed a reduction in both pain and fatigue, which is also reported in trials of anti-TNF agents in AS (28), there-
Table 4 Before and After Compared to Controls Over Study of Before and After the Prescription of Anti-TNF
Anti-TNF treated (n ⫽ 39) Fatigue Male patients (n ⫽ 29) Female patients (n ⫽ 10) Pain BASDAI Control (n ⫽ 196) Fatigue Male patients (n ⫽ 154) Female patients (n ⫽ 41) Pain BASDAI
Baseline (SD)
Follow-Up (SD)
(No anti-TNF) 66.2 (26) 65.4 (27.4) 68.1 (26.5) 64.7 (24.2) 58.9 (23.7) (No anti-TNF) 46.6 (28.4) 45.4 (28.2) 50.8 (29.5) 45.1 (29.9) 39.2 (24.0)
(Anti-TNF) 51.8 (29) 49.7 (28.5) 61.6 (27.5) 54.4 (28.7) 46.6 (26.2) (No anti-TNF) 44.8 (28.0) 42.1 (27.6) 54.7 (26.6) 45.2 (30.0) 38.7 (23.7)
Difference (95% CI)
Significance P Value
14.4 (5.3 to 23.5) 15.7 (4.2 to 27.3) 6.5 (⫺7.7 to 20.7) 10.2 (0.47 to 20.0) 12.3 (4.2 to 20.3)
0.0028 0.0095 0.3 0.04 0.0039
1.77 (⫺1.6 to 5.2) 3.3 (⫺0.5 to 7.1) ⫺4.0 (⫺11.6 to 3.7) ⫺0.1 (⫺0.3 to 0.1) 0.49 (⫺2.26 to 3.2)
0.3 0.9 0.3 0.3 0.7
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fore, supporting the finding that interventions that target disease activity will alleviate fatigue. It is likely that antiTNF affects the inflammatory pathways that are common to pain and fatigue pathways. The finding that alleviating fatigue needs to focus on targeting pain is supported by findings from other studies. For example, recent work in osteoarthritis (29) found that pain determined depressed mood through its effect on fatigue and disability. This study concluded that there is a need for improved pain management to prevent downstream effects on disability and mood. Pain is the most powerful predictor of fatigue (13,16), and effective disease-modifying therapy, namely, anti-TNF, has been shown to improve sleep (30) and fatigue (31,32). In RA, however, a recent meta-analysis has suggested that the overall effect of biologic therapies on fatigue in RA, although significant, is relatively small (33). This is consistent with our results where, despite an improvement in levels of fatigue and pain, the AS patients on anti-TNF still had significant residual fatigue (mean 51.8 on a scale of 0-100) and pain (mean 54.4 on a scale of 0-100). The anti-TNF improved fatigue by 14% and pain by only 10%, suggesting in this group of patients that although the minimal clinically important difference was reached (34), the majority of the factors causing the disease activity have not been addressed. This is also consistent with the complex causality of fatigue in chronic inflammatory conditions (35), which include “central” fatigue (36,37), which may be unaffected by peripheral immunosuppression. Thus, other pain management strategies may prove beneficial in alleviating fatigue. For example, mindfulness-based stress reduction (MBSR) has been shown to be of benefit in coping with a variety of chronic conditions associated with disability (38). In particular, MBSR was originally introduced into clinical practice as an intervention for chronic pain (39) and the evidence for MBSR improving acceptance of pain and the associated well-being and physical function is growing (40). For example, in multiple sclerosis, where people experience musculoskeletal and neurogenic pain, MBSR has been shown to improve the quality of life with particular benefits for fatigue (41) and there have been calls for assessing nonpharmaceutical treatments such as cognitive behavioral therapy and graded exercise directly on their effect on fatigue in RA, lupus, and fibromyalgia (42). Therefore, perhaps there should also be assessment of these therapies for fatigue in AS. Strengths and Limitations of the Study The response rate for this questionnaire was high (90%) and this may be indicative of the importance fatigue plays in the lives of people with AS. However, it is possible that the patients who dropped out of the cohort may have had different responses to those remaining within the cohort. We do not have an objective assessment of fatigue and rely on a subjective self-report. There are currently no biochemical markers that can be used to assess fatigue levels objectively. Therefore, the 2 main factors studied in this
Fatigue in ankylosing spondylitis
study, namely pain and fatigue, are subjective self-reported outcomes. However, we have tried to overcome limitations in day-to-day subjective changes in fatigue and pain levels by taking an average of 3 questionnaires spanning a 6-month period of disease. This study used open-ended questions to give a first impression of qualitative aspects of fatigue. However, interviews and focus groups can offer more detailed exploration that can be given by open-ended questions and we have now performed focus groups within this study and will be publishing these findings separately. The patients prescribed anti-TNF were younger with high disease activity compared to non-TNF patients. Thus, although TNF reduced fatigue in this group, it is possible that in these patients fatigue was more strongly linked to pain/activity and that fatigue in the non-TNF group may have different causal factors. In conclusion, this study finds that fatigue is a major aspect of the disease activity and is strongly associated with pain but that 63% of the variation in fatigue still remains unexplained. Anti-TNF medication does reduce fatigue but residual fatigue and pain still remain. Strategies to alleviate fatigue should focus on interventions that target the pain with perhaps a focus on targeting pain management with therapies such as mindfulness and cognitive behavioral therapy. ACKNOWLEDGMENTS This study was funded by the Medical Research Council (MRC) and the National Institute for Social Care and Health Research (NISCHR). We would like to thank all the people with ankylosing spondylitis who have participated in the study. APPENDIX. SUPPLEMENTARY DATA Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/ 10.1016/j.semarthrit.2012.06.002. REFERENCES 1. Krupp LB, Pollina DA. Mechanisms and management of fatigue in progressive neurological disorders. Curr Opin Neurol 1996; 9(6):456-60. 2. Ibn Yacoub Y, Amine B, Laatiris A, Abouqal R, Hajjaj-Hassouni N. Assessment of fatigue in Moroccan patients with ankylosing spondylitis. Clin Rheumatol 2010;29(11):1295-9. 3. Swain MG. Fatigue in chronic disease. Clin Sci (Lond) 2000; 99(1):1-8. 4. Trendall J. Concept analysis: Chronic fatigue. J Adv Nurs 2000; 32(5):1126-31. 5. Belza B. The impact of fatigue on exercise performance. Arthritis Care Res 1994;7(4):176-80. 6. Repping-Wuts H, Fransen J, van Achterberg T, Bleijenberg G, van Riel P. Persistent severe fatigue in patients with rheumatoid arthritis. J Clin Nurs 2007;16(11C):377-83. 7. Smith RD, Polley HF. Rest therapy for rheumatoid arthritis. Mayo Clin Proc 1978;53(3):141-5.
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