The impact of disease activity, pain, disability and treatments on fatigue in established rheumatoid arthritis

Campbell, Richard C.; Batley, M.; Hammond, Anthony; Ibrahim, Fowzia; Kingsley, Gabrielle; Scott, David

doi:10.1007/s10067-011-1887-y

Cited by 39 publications

(51 citation statements)

References 19 publications

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“…Of the 3 PROs we evaluated, fatigue was the least likely to improve. Other studies have also found that fatigue is resistant to improvement during therapy 26, 27. Nevertheless, 38.5% of patients who remained on therapy in our study did experience a significant response in fatigue after 12 months of adalimumab treatment, in agreement with other studies of the effect of anti‐TNF agents, including adalimumab, on fatigue 28, 29.…”

Section: Discussionsupporting

confidence: 91%

Association of Improvement in Pain With Therapeutic Response as Determined by Individual Improvement Criteria in Patients With Rheumatoid Arthritis

Scharbatke

Behrens

Schmalzing

et al. 2016

Arthritis Care & Research

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ObjectiveTo use statistical methods to establish a threshold for individual response in patient‐reported outcomes (PROs) in patients with rheumatoid arthritis.MethodsWe used an analysis of variance model in patients on stable therapy (discovery cohort) to establish critical differences (dcrit) for the minimum change associated with a significant individual patient response (beyond normal variation) in the PRO measures of pain (0–10), fatigue (0–10), and function (Funktionsfragebogen Hannover questionnaire; 0–100). We then evaluated PRO responses in patients initiating adalimumab in a noninterventional study (treatment cohort).ResultsIn the discovery cohort (n = 700), PROs showed excellent long‐term retest reliability. The minimum change that exceeded random fluctuation was conservatively determined to be 3 points for pain, 4 points for fatigue, and 16 points for function. In the treatment cohort (n = 2,788), 1,483 patients (53.2%) achieved a significant individual therapeutic response as assessed by Disease Activity Score in 28 joints (DAS28)–dcrit (≥1.8 points) after 12 months of adalimumab treatment; 68.5% of patients with a DAS28‐dcrit response achieved a significant improvement in pain, whereas approximately 40% achieved significant improvements in fatigue or function. Significant improvements in all 3 PROs occurred in 22.7% of patients; 22.8% did not have any significant PRO responses. In contrast, significant improvements in all 3 PROs occurred in only 4.4% of 1,305 patients who did not achieve a DAS28‐dcrit response at month 12, and 59.1% did not achieve any significant PRO responses.ConclusionThe establishment of critical differences in PROs distinguishes true responses from random variation and provides insights into appropriate patient management.

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Section: Discussionsupporting

confidence: 91%

Association of Improvement in Pain With Therapeutic Response as Determined by Individual Improvement Criteria in Patients With Rheumatoid Arthritis

Scharbatke

Behrens

Schmalzing

et al. 2016

Arthritis Care & Research

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“…Furthermore, the interrelations between the outcomes and the relative importance of explanatory variables may also be influenced by the characteristics of the RA patients, including disease stage and activity [31]. The present study examined associations between PaGl, pain, and fatigue as scored on VAS in a well-characterized sample of DMARD-treated RA patients from the daily clinic initiating biological treatment due to active and uncontrolled disease activity.…”

Section: Discussionmentioning

confidence: 97%

Interplay between patient global assessment, pain, and fatigue and influence of other clinical disease activity measures in patients with active rheumatoid arthritis

Egsmose

Madsen

2015

Clin Rheumatol

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The interplay between patient-reported outcome measures in rheumatology is not well clarified. The objective of the study was to examine associations on the group level and concordance on the individual patient level between patient global assessment (PaGl), pain, and fatigue as scored on visual analog scales (VAS) in the daily clinic by patients with active rheumatoid arthritis (RA). Associations with other measures of disease activity were also examined. Traditional disease activity data on 221 RA patients with active disease planned to initiate biological treatment were extracted from the Danish DANBIO registry. Associations between VAS PaGl, pain, and fatigue (0-100) were examined using multiple regression analysis. Concordance between the VAS scores was expressed as the bias (mean difference between intra-individual scores) and the 95% lower and upper limits of agreement (LLoA; ULoA) according to the Bland-Altman method. Mean age was 57 ± 14 years, mean Disease Activity Score (DAS28-CRP4) 5.0 ± 0.9, and mean PaGl 63.6 ± 22.6. PaGl was most strongly predicted by pain and fatigue, pain by PaGl and fatigue, and fatigue by PaGl and pain (beta ranging from 0.17 to 0.69, p < 0.01-0.0001). More objective measures were not or far less predictive. LLoA;ULoA [bias] for PaGl vs. pain was -19.1; 29.5 [5.2], for PaGl vs. fatigue -22.8; 28.6 [2.9], and for fatigue vs. pain -29.2; 33.8 [2.3]. In conclusion, PaGl, pain, and fatigue were most strongly explained by each other, not by more objective clinical measures of disease activity and were nearly identical on the group level. On the individual patient level, however, differences between the scores varied considerably. The findings highlight the challenge of understanding and dealing with traditional patient-reported VAS measures when it comes to individual RA patients in the daily clinic.

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“…Higher baseline fatigue is reported in patients with RA initiating TNF inhibitor therapy as opposed to traditional synthetic DMARDs (17,21), while a similar fatigue response to treatment among patients treated with either synthetic DMARDs or TNF inhibitors is also reported (17,22). It is not known if the nature and origin of fatigue or if the impact of synthetic DMARDs versus TNF inhibitors on fatigue differ at different stages of the disease (22). Despite the multitude of published studies on the efficacy of biologic DMARDs, few have measured fatigue with respect to TNF inhibitor therapies (17,23,24).…”

Section: Introductionmentioning

confidence: 96%

“…While a relationship between disease activity and fatigue is recognized, pain and TJC are also seen as predictors of fatigue in IA (17), so too are function and psychosocial variables (18 -20). Higher baseline fatigue is reported in patients with RA initiating TNF inhibitor therapy as opposed to traditional synthetic DMARDs (17,21), while a similar fatigue response to treatment among patients treated with either synthetic DMARDs or TNF inhibitors is also reported (17,22). It is not known if the nature and origin of fatigue or if the impact of synthetic DMARDs versus TNF inhibitors on fatigue differ at different stages of the disease (22).…”

Section: Introductionmentioning

confidence: 99%

How Much Is Fatigue Explained by Standard Clinical Characteristics of Disease Activity in Patients With Inflammatory Arthritis? A Longitudinal Study

Minnock

McKee

Bresnihan³

et al. 2014

Arthritis Care & Research

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Objective. To determine the relationship between fatigue and the American College of Rheumatology (ACR) core set outcomes in patients with inflammatory arthritis (IA).Methods. This prospective longitudinal study evaluated fatigue in patients with active IA commencing tumor necrosis factor (TNF) inhibitor therapy. Fatigue was assessed using the multidimensional assessment of fatigue scale and the ACR core set (swollen and tender joint counts, pain, global health score, Health Assessment Questionnaire [HAQ] disability index [DI], and C-reactive protein level) was used for standard assessment of disease activity. Results. Assessments at baseline, 3 months, and 6 months were completed by 125, 92, and 82 patients, respectively. Fatigue and disease activity improved significantly within the first 3 months, with fatigue improving by 29% (F[2, 118] ‫؍‬ 17.14, P < 0.001; repeated-measures analysis of variance). Using multiple regression, the amount of fatigue explained by the core outcomes differed at each time point: 28% at baseline (P < 0.001; significant predictors were the HAQ DI, global health, and C-reactive protein level), 37% at 3 months (P < 0.001; significant predictors were pain and tender joint count), and 46% at 6 months (P < 0.001; significant predictor was global health). Regression modelling using the fatigue change score at 3 months explained 17% of fatigue change (P < 0.012; significant predictors were HAQ DI and global health). Conclusion. Fatigue, which improved following treatment with TNF inhibitors, was poorly and inconsistently explained through the core set outcomes. Further, fatigue was least accounted for when the disease was most active, highlighting the need for further research into alternate explanations. These findings suggest further exploration of contributing variables and mechanisms in order to develop targeted symptom management of fatigue in IA.

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The impact of disease activity, pain, disability and treatments on fatigue in established rheumatoid arthritis

Cited by 39 publications

References 19 publications

Association of Improvement in Pain With Therapeutic Response as Determined by Individual Improvement Criteria in Patients With Rheumatoid Arthritis

Association of Improvement in Pain With Therapeutic Response as Determined by Individual Improvement Criteria in Patients With Rheumatoid Arthritis

Interplay between patient global assessment, pain, and fatigue and influence of other clinical disease activity measures in patients with active rheumatoid arthritis

How Much Is Fatigue Explained by Standard Clinical Characteristics of Disease Activity in Patients With Inflammatory Arthritis? A Longitudinal Study

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