Construction of a US fibromyalgia registry using the Fibromyalgia Research Survey criteria

Evaluation of the Fibromyalgia and Related Risk Factors in Patients with Advanced Kidney Failure Undergoing Hemodialysis

BACKGROUND

Fibromyalgia syndrome (FMS) is defined as widespread and persistent pain in the musculoskeletal system. There are limited reports regarding the prevalence of fibromyalgia syndrome in patients with advanced kidney failure undergoing regular hemodialysis. Therefore, this study aimed to evaluate the prevalence of fibromyalgia syndrome and its risk factors in a large proportion of patients under the hemodialysis condition.

MATERIALS AND METHODS

In this cross-sectional study, 293 patients who were admitted to the hemodialysis ward were evaluated for fibromyalgia syndrome in an educational hospital. The questionnaire was designed according to symptom severity score (SS score) and widespread pain index (WPI) criteria. The correlation between FMS and various variables, including demographic, clinical, and biochemistry biomarkers, was also precisely calculated by logistic regression. Data were analyzed using SPSS v.17 statistics software.

RESULTS

The results showed that, of 293 hemodialysis patients, 130 patients (44.4%) had fibromyalgia, the mean age of patients with and without fibromyalgia was 61.09 ± 15.36 and 53.49 ± 15.38 years old, respectively (P = 0.001). Moreover, there was a significant difference in terms of gender among patients with fibromyalgia syndrome (P = 0.001). To note, there was no significant relationship between the kidney failure etiopathogenesis, duration of dialysis, body mass index (BMI), Kt/v index, history of peritoneal dialysis, and laboratory parameters with fibromyalgia in hemodialysis patients (P > 0.05). However, our findings revealed that both age and gender could be considered as the predictor variables associated with fibromyalgia in patients undergoing hemodialysis.

CONCLUSION

Taken together, in this study, we found that age and gender would be the critical factors in terms of the fibromyalgia syndrome in patients undergoing hemodialysis.

Longitudinal stability of fibromyalgia symptom clusters

Background

Using self-report questionnaires of key fibromyalgia symptom domains (pain, fatigue, sleep disturbance, function, stiffness, dyscognition, depression, and anxiety), we previously identified four unique symptom clusters. The purpose of this study was to examine the stability of fibromyalgia symptom clusters between baseline and 2-year follow-up.

Methods

Women with a diagnosis of fibromyalgia completed the Brief Pain Inventory, Profile of Mood States, Medical Outcomes Study Sleep measure, Multidimensional Fatigue Inventory, Multiple Ability Self-Report Questionnaire, Revised Fibromyalgia Impact Questionnaire, and the 36-Item Short Form Survey Instrument at baseline. Follow-up measures were completed approximately 2 years later. The hierarchical agglomerative clustering algorithm previously developed was applied; agreement between baseline and follow-up was assessed with the κ statistic.

Results

Among 433 participants, the mean age was 56 (range 20–85) years. The median Revised Fibromyalgia Impact Questionnaire total score was 57 (range 8–96). More than half of participants (58%) remained in the same cluster at follow-up as at baseline, which represented moderate agreement between baseline and follow-up (κ = 0.44, 95% confidence interval (CI) 0.37–0.50). Only two patients changed from high symptom intensity to low symptom intensity; similarly, only three moved from low to high.

Conclusions

Fibromyalgia patients classified into four unique symptom clusters based on the key domains of pain, fatigue, sleep disturbance, function, stiffness, dyscognition, depression, and anxiety showed moderate stability in cluster assignment after 2 years. Few patients moved between the two extremes of severity, and it was slightly more common to move to a lower symptom level than to worsen.

Trial registration

Not applicable.

The PROMIS fatigue item bank has good measurement properties in patients with fibromyalgia and severe fatigue

PURPOSE

Efficient management of fibromyalgia (FM) requires precise measurement of FM-specific symptoms. Our objective was to assess the measurement properties of the Patient-Reported Outcome Measurement Information System (PROMIS) fatigue item bank (FIB) in people with FM.

METHODS

We applied classical psychometric and item response theory methods to cross-sectional PROMIS-FIB data from two samples. Data on the clinical FM sample were obtained at a tertiary medical center. Data for the U.S. general population sample were obtained from the PROMIS network. The full 95-item bank was administered to both samples. We investigated dimensionality of the item bank in both samples by separately fitting a bifactor model with two group factors; experience and impact. We assessed measurement invariance between samples, and we explored an alternate factor structure with the normative sample and subsequently confirmed that structure in the clinical sample. Finally, we assessed whether reporting FM subdomain scores added value over reporting a single total score.

RESULTS

The item bank was dominated by a general fatigue factor. The fit of the initial bifactor model and evidence of measurement invariance indicated that the same constructs were measured across the samples. An alternative bifactor model with three group factors demonstrated slightly improved fit. Subdomain scores add value over a total score.

CONCLUSIONS

We demonstrated that the PROMIS-FIB is appropriate for measuring fatigue in clinical samples of FM patients. The construct can be presented by a single score; however, subdomain scores for the three group factors identified in the alternative model may also be reported.

Fibromyalgia Flares: A Qualitative Analysis

OBJECTIVE

Patients with fibromyalgia report periods of symptom exacerbation, colloquially referred to as "flares" and despite clinical observation of flares, no research has purposefully evaluated the presence and characteristics of flares in fibromyalgia. The purpose of this qualitative study was to describe fibromyalgia flares in a sample of patients with fibromyalgia.

METHODS

Using seven open-ended questions, patients were asked to describe how they perceived fibromyalgia flares and triggers and alleviating factors associated with flares. Patients were also asked to describe how a flare differs from their typical fibromyalgia symptoms and how they cope with fibromyalgia flares. Content analysis was used to analyze the text.

RESULTS

A total of 44 participants completed the survey. Responses to the seven open-ended questions revealed three main content areas: causes of flares, flare symptoms, and dealing with a flare. Participants identified stress, overdoing it, poor sleep, and weather changes as primary causes of flares. Symptoms characteristic of flares included flu-like body aches/exhaustion, pain, fatigue, and variety of other symptoms. Participants reported using medical treatments, rest, activity and stress avoidance, and waiting it out to cope with flares.

CONCLUSIONS

Our results demonstrate that periods of symptom exacerbation (i.e., flares) are commonly experienced by patients with fibromyalgia and symptoms of flares can be differentiated from every day or typical symptoms of fibromyalgia. Our study is the first of its kind to qualitatively explore characteristics, causes, and management strategies of fibromyalgia flares. Future studies are needed to quantitatively characterize fibromyalgia flares and evaluate mechanisms of flares.

Psychological Resilience, Affective Mechanisms, and Symptom Burden in a Tertiary Care Sample of Patients with Fibromyalgia

Research demonstrates that patients with fibromyalgia who have higher positive and lower negative affect have lower symptom burden. Affect has been shown to be associated with resilience. This study examined the relationship between affect, resilience and fibromyalgia symptom burden in a clinical sample of patients with fibromyalgia. We hypothesized that (a) positive and negative affect would be associated with fibromyalgia symptom burden; (b) resilience would be associated with positive and negative affect; (c) resilience would be associated with fibromyalgia symptom burden; and (d) the connection between resilience and fibromyalgia symptom burden would be mediated by both positive and negative affect. A sample of 858 patients with fibromyalgia completed questionnaires. Mediation modelling revealed statistically significant direct effects of resilience on fibromyalgia symptom burden (β = -0.10, P < 0.001) and statistically significant indirect effects of resilience on fibromyalgia symptom burden through affect (β = -0.36, P < 0.001), suggesting that both resilience and affect influence fibromyalgia symptom burden. Our results suggest that improving affect through resiliency training could be studied as a modality for improving fibromyalgia symptom burden.

Fibromyalgia

Fibromyalgia is a common illness characterized by chronic widespread pain, sleep problems (including unrefreshing sleep), physical exhaustion and cognitive difficulties. The definition, pathogenesis and treatment are controversial, and some even contest the existence of this disorder. In 1990, the American College of Rheumatology (ACR) defined classification criteria that required multiple tender points (areas of tenderness occurring in muscles and muscle-tendon junctions) and chronic widespread pain. In 2010, the ACR preliminary diagnostic criteria excluded tender points, allowed less extensive pain and placed reliance on patient-reported somatic symptoms and cognitive difficulties. Fibromyalgia occurs in all populations worldwide, and symptom prevalence ranges between 2% and 4% in the general population. The prevalence of people who are actually diagnosed with fibromyalgia ('administrative prevalence') is much lower. A model of fibromyalgia pathogenesis has been suggested in which biological and psychosocial variables interact to influence the predisposition, triggering and aggravation of a chronic disease, but the details are unclear. Diagnosis requires the history of a typical cluster of symptoms and the exclusion of a somatic disease that sufficiently explains the symptoms by medical examination. Current evidence-based guidelines emphasize the value of multimodal treatments, which encompass both non-pharmacological and selected pharmacological treatments tailored to individual symptoms, including pain, fatigue, sleep problems and mood problems. For an illustrated summary of this Primer, visit: http://go.nature.com/LIBdDX.

Frequency of Migraine Headaches in Patients With Fibromyalgia

OBJECTIVE

The purpose of this study was to evaluate the frequency of migraine headache in a large cohort of patients with fibromyalgia using a brief migraine headache-screening tool.

BACKGROUND

Several studies report a high prevalence of fibromyalgia among patients with migraine headaches, but there is a dearth of research evaluating the frequency of migraine headaches in patients with fibromyalgia, despite clinical observations suggesting that migraine headaches are common in patients with fibromyalgia.

DESIGN AND METHODS

This was a cross-sectional survey study. Patients (N = 3717) with a previous diagnosis of fibromyalgia who were members of the Mayo Clinic Fibromyalgia Registry were contacted by electronic survey and asked to complete a brief demographic and medical history questionnaire and the validated ID-Migraine screener.

RESULTS

A total of 1730 patients (46.5%) completed the electronic survey. The majority of participants were white (97.2%), female (92.5%), with a mean age of 56.2 (±13.1) years. Of the respondents, 966 (55.8%) met criteria for migraine headaches. Hypertension (309 [32.3%] vs. 294 [40.1%], P = .004), asthma (312 [32.5%] vs. 189 [25.9%], P = .011), irritable bowel syndrome (520 [54.6%] vs. 348 [47.6], P = .017), chronic fatigue syndrome (486 [50.7%] vs. 271 [37.1], P < .0001), depression (634 [66.5%] vs. 413 [56.7%], P = .0002), anxiety (415 [43.5%] vs. 252 [34.7%], P = .0011), and post-traumatic stress disorder (172 [18.0%] vs. 96 [13.2%], P = .006) were all significantly more common in those who met criteria for migraine headaches than those who did not.

CONCLUSION

The results of this study suggest that migraine headaches are common in patients with fibromyalgia. Clinicians who care for either population must be aware that these conditions commonly overlap and can significantly increase a patient's cumulative disease burden.

OMERACT-based fibromyalgia symptom subgroups: an exploratory cluster analysis

Introduction

The aim of this study was to identify subsets of patients with fibromyalgia with similar symptom profiles using the Outcome Measures in Rheumatology (OMERACT) core symptom domains.

Methods

Female patients with a diagnosis of fibromyalgia and currently meeting fibromyalgia research survey criteria completed the Brief Pain Inventory, the 30-item Profile of Mood States, the Medical Outcomes Sleep Scale, the Multidimensional Fatigue Inventory, the Multiple Ability Self-Report Questionnaire, the Fibromyalgia Impact Questionnaire–Revised (FIQ-R) and the Short Form-36 between 1 June 2011 and 31 October 2011. Hierarchical agglomerative clustering was used to identify subgroups of patients with similar symptom profiles. To validate the results from this sample, hierarchical agglomerative clustering was repeated in an external sample of female patients with fibromyalgia with similar inclusion criteria.

Results

A total of 581 females with a mean age of 55.1 (range, 20.1 to 90.2) years were included. A four-cluster solution best fit the data, and each clustering variable differed significantly (P <0.0001) among the four clusters. The four clusters divided the sample into severity levels: Cluster 1 reflects the lowest average levels across all symptoms, and cluster 4 reflects the highest average levels. Clusters 2 and 3 capture moderate symptoms levels. Clusters 2 and 3 differed mainly in profiles of anxiety and depression, with Cluster 2 having lower levels of depression and anxiety than Cluster 3, despite higher levels of pain. The results of the cluster analysis of the external sample (n = 478) looked very similar to those found in the original cluster analysis, except for a slight difference in sleep problems. This was despite having patients in the validation sample who were significantly younger (P <0.0001) and had more severe symptoms (higher FIQ-R total scores (P = 0.0004)).

Conclusions

In our study, we incorporated core OMERACT symptom domains, which allowed for clustering based on a comprehensive symptom profile. Although our exploratory cluster solution needs confirmation in a longitudinal study, this approach could provide a rationale to support the study of individualized clinical evaluation and intervention.

A Comparison of Fibromyalgia Symptoms in Patients with Healthy versus Depressive, Low and Reactive Affect Balance Styles

BACKGROUND AND AIMS

Affect balance reflects relative levels of negative affect (NA) and positive affect (PA) and includes four styles: Healthy (low NA/high PA), Depressive (high NA/low PA), Reactive (high NA/high PA) and Low (low NA/low PA). These affect balance styles may have important associations with clinical outcomes in patients with fibromyalgia. Herein, we evaluated the severity of core fibromyalgia symptom domains as described by the Outcomes Research in Rheumatology-Fibromyalgia working group in the context of the four affect balance styles.

METHODS

Data from735 patients with fibromyalgia who completed the Brief Pain Inventory, Multidimensional Fatigue Inventory, Profile of Mood States, Medical Outcomes Sleep Scale, Multiple Ability Self-Report Questionnaire, Fibromyalgia Impact Questionnaire-Revised, Medical Outcomes Study Short Form-36, and Positive and Negative Affect Schedule were included in this analysis.

RESULTS

The majority (51.8%) of patients in our sample had a Depressive affect balance style; compared to patients with a Healthy affect balance style, they scored significantly worse in all fibromyalgia symptom domains including pain, fatigue, sleep disturbance, dyscognition, depression, anxiety, stiffness, and functional status (P = <.001 - .004). Overall, patients with a Healthy affect balance style had the lowest level of symptoms, while symptom levels of those with Reactive and Low affect balance styles were distributed in between those of the Depressive and Healthy groups.

CONCLUSIONS AND IMPLICATIONS

The results of our cross-sectional study suggest that having a Healthy affect balance style is associated with better physical and psychological symptom profiles in fibromyalgia. Futures studies evaluating these associations longitudinally could provide rationale for evaluating the effect of psychological interventions on affect balance and clinical outcomes in fibromyalgia.