The epidemiology of psoriatic arthritis in the UK: a health intelligence analysis of UK Primary Care Electronic Health Records 1991-2020.

OBJECTIVES: Epidemiological estimates of psoriatic arthritis (PsA) underpin the provision of healthcare, research, and the work of government, charities and patient organizations. Methodological problems impacting prior estimates include small sample sizes, incomplete case ascertainment, and representativeness. We developed a statistical modelling strategy to provide contemporary prevalence and incidence estimates of PsA from 1991 to 2020 in the UK. METHODS: Data from Clinical Practice Research Datalink (CPRD) were used to identify cases of PsA between 1st January 1991 and 31st December 2020. To optimize ascertainment, we identified cases of Definite PsA (≥1 Read code for PsA) and Probable PsA (satisfied a bespoke algorithm). Standardized annual rates were calculated using Bayesian multilevel regression with post-stratification to account for systematic differences between CPRD data and the UK population, based on age, sex, socioeconomic status and region of residence. RESULTS: A total of 26293 recorded PsA cases (all definitions) were identified within the study window (77.9% Definite PsA). Between 1991 and 2020 the standardized prevalence of PsA increased twelve-fold from 0.03 to 0.37. The standardized incidence of PsA per 100,000 person years increased from 8.97 in 1991 to 15.08 in 2020, an almost 2-fold increase. Over time, rates were similar between the sexes, and across socioeconomic status. Rates were strongly associated with age, and consistently highest in Northern Ireland. CONCLUSION: The prevalence and incidence of PsA recorded in primary care has increased over the last three decades. The modelling strategy presented can be used to provide contemporary prevalence estimates for musculoskeletal disease using routinely collected primary care data.

What do people living with chronic pain want from a pain forecast? A research prioritization study.

Because people with chronic pain feel uncertain about their future pain, a pain-forecasting model could support individuals to manage their daily pain and improve their quality of life. We conducted two patient and public involvement activities to design the content of a pain-forecasting model by learning participants' priorities in the features provided by a pain forecast and understanding the perceived benefits that such forecasts would provide. The first was a focus group of 12 people living with chronic pain to inform the second activity, a survey of 148 people living with chronic pain. Respondents prioritized forecasting of pain flares (100, or 68%) and fluctuations in pain severity (94, or 64%), particularly the timing of the onset and the severity. Of those surveyed, 75% (or 111) would use a future pain forecast and 80% (or 118) perceived making plans (e.g., shopping, social) as a benefit. For people with chronic pain, the timing of the onset of pain flares, the severity of pain flares and fluctuations in pain severity were prioritized as being key features of a pain forecast, and making plans was prioritized as being a key benefit.

Gender equity in academic rheumatology, current status and potential for improvement: a cross-sectional study to inform an EULAR task force.

OBJECTIVES: Evidence on the current status of gender equity in academic rheumatology in Europe and potential for its improvement is limited. The EULAR convened a task force to obtain empirical evidence on the potential unmet need for support of female rheumatologists, health professionals and non-clinical scientists in academic rheumatology. METHODS: This cross-sectional study comprised three web-based surveys conducted in 2020 among: (1) EULAR scientific member society leaders, (2) EULAR and Emerging EULAR Network (EMEUNET) members and (3) EULAR Council members. Statistics were descriptive with significance testing for male/female responses assessed by χ2 test and t-test. RESULTS: Data from EULAR scientific member societies in 13 countries indicated that there were disproportionately fewer women in academic rheumatology than in clinical rheumatology, and they tended to be under-represented in senior academic roles. From 324 responses of EULAR and EMEUNET members (24 countries), we detected no gender differences in leadership aspirations, self-efficacy in career advancement and work-life integration as well as the share of time spent on research, but there were gender differences in working hours and the levels of perceived gender discrimination and sexual harassment. There were gender differences in the ranking of 7 of 26 factors impacting career advancement and of 8 of 24 potential interventions to aid career advancement. CONCLUSIONS: There are gender differences in career advancement in academic rheumatology. The study informs a EULAR task force developing a framework of potential interventions to accelerate gender-equitable career advancement in academic rheumatology.

Remote sampling of biomarkers of inflammation with linked patient generated health data in patients with rheumatic and musculoskeletal diseases: an Ecological Momentary Assessment feasibility study.

BACKGROUND: People with rheumatic diseases experience troublesome fluctuations in fatigue. Debated causes include pain, mood and inflammation. To determine the relationships between these potential causes, serial assessments are required but are methodologically challenging. This mobile health (mHealth) study explored the viability of using a smartphone app to collect patient-reported symptoms with contemporaneous Dried Blood Spot Sampling (DBSS) for inflammation. METHODS: Over 30 days, thirty-eight participants (12 RA, 13 OA, and 13 FM) used uMotif, a smartphone app, to report fatigue, pain and mood, on 5-point ordinal scales, twice daily. Daily DBSS, from which C-reactive Protein (CRP) values were extracted, were completed on days 1-7, 14 and 30. Participant engagement was determined based on frequency of data entry and ability to calculate within- and between-day symptom changes. DBSS feasibility and engagement was determined based on the proportion of samples returned and usable for extraction, and the number of days between which between-day changes in CRP which could be calculated (days 1-7). RESULTS: Fatigue was reported at least once on 1085/1140 days (95.2%). Approximately 65% of within- and between-day fatigue changes could be calculated. Rates were similar for pain and mood. A total of 287/342 (83.9%) DBSS, were returned, and all samples were viable for CRP extraction. Fatigue, pain and mood varied considerably, but clinically meaningful (≥ 5 mg/L) CRP changes were uncommon. CONCLUSIONS: Embedding DBSS in mHealth studies will enable researchers to obtain serial symptom assessments with matched biological samples. This provides exciting opportunities to address hitherto unanswerable questions, such as elucidating the mechanisms of fatigue fluctuations.

Smartphones for musculoskeletal research - hype or hope? Lessons from a decennium of mHealth studies.

BACKGROUND: Smartphones provide opportunities for musculoskeletal research: they are integrated in participants' daily lives and can be used to collect patient-reported outcomes as well as sensor data from large groups of people. As the field of research with smartphones and smartwatches matures, it has transpired that some of the advantages of this modern technology are in fact double-edged swords. BODY: In this narrative review, we illustrate the advantages of using smartphones for data collection with 18 studies from various musculoskeletal domains. We critically appraised existing literature, debunking some myths around the advantages of smartphones: the myth that smartphone studies automatically enable high engagement, that they reach more representative samples, that they cost little, and that sensor data is objective. We provide a nuanced view of evidence in these areas and discuss strategies to increase engagement, to reach representative samples, to reduce costs and to avoid potential sources of subjectivity in analysing sensor data. CONCLUSION: If smartphone studies are designed without awareness of the challenges inherent to smartphone use, they may fail or may provide biased results. Keeping participants of smartphone studies engaged longitudinally is a major challenge. Based on prior research, we provide 6 actions by researchers to increase engagement. Smartphone studies often have participants that are younger, have higher incomes and high digital literacy. We provide advice for reaching more representative participant groups, and for ensuring that study conclusions are not plagued by bias resulting from unrepresentative sampling. Costs associated with app development and testing, data storage and analysis, and tech support are substantial, even if studies use a 'bring your own device'-policy. Exchange of information on costs, collective app development and usage of open-source tools would help the musculoskeletal community reduce costs of smartphone studies. In general, transparency and wider adoption of best practices would help bringing smartphone studies to the next level. Then, the community can focus on specific challenges of smartphones in musculoskeletal contexts, such as symptom-related barriers to using smartphones for research, validating algorithms in patient populations with reduced functional ability, digitising validated questionnaires, and methods to reliably quantify pain, quality of life and fatigue.

Sleep Disturbance and Quality of Life in Rheumatoid Arthritis: Prospective mHealth Study.

BACKGROUND: Sleep disturbances and poor health-related quality of life (HRQoL) are common in people with rheumatoid arthritis (RA). Sleep disturbances, such as less total sleep time, more waking periods after sleep onset, and higher levels of nonrestorative sleep, may be a driver of HRQoL. However, understanding whether these sleep disturbances reduce HRQoL has, to date, been challenging because of the need to collect complex time-varying data at high resolution. Such data collection is now made possible by the widespread availability and use of mobile health (mHealth) technologies. OBJECTIVE: This mHealth study aimed to test whether sleep disturbance (both absolute values and variability) causes poor HRQoL. METHODS: The quality of life, sleep, and RA study was a prospective mHealth study of adults with RA. Participants completed a baseline questionnaire, wore a triaxial accelerometer for 30 days to objectively assess sleep, and provided daily reports via a smartphone app that assessed sleep (Consensus Sleep Diary), pain, fatigue, mood, and other symptoms. Participants completed the World Health Organization Quality of Life-Brief (WHOQoL-BREF) questionnaire every 10 days. Multilevel modeling tested the relationship between sleep variables and the WHOQoL-BREF domains (physical, psychological, environmental, and social). RESULTS: Of the 268 recruited participants, 254 were included in the analysis. Across all WHOQoL-BREF domains, participants' scores were lower than the population average. Consensus Sleep Diary sleep parameters predicted the WHOQoL-BREF domain scores. For example, for each hour increase in the total time asleep physical domain scores increased by 1.11 points (ß=1.11, 95% CI 0.07-2.15) and social domain scores increased by 1.65 points. These associations were not explained by sociodemographic and lifestyle factors, disease activity, medication use, anxiety levels, sleep quality, or clinical sleep disorders. However, these changes were attenuated and no longer significant when pain, fatigue, and mood were included in the model. Increased variability in total time asleep was associated with poorer physical and psychological domain scores, independent of all covariates. There was no association between actigraphy-measured sleep and WHOQoL-BREF. CONCLUSIONS: Optimizing total sleep time, increasing sleep efficiency, decreasing sleep onset latency, and reducing variability in total sleep time could improve HRQoL in people with RA.

Predicting relapse in anti-neutrophil cytoplasmic antibody-associated vasculitis: a Systematic review and meta-analysis.

OBJECTIVES: Relapses affect 30-50% of patients with ANCA-associated vasculitis (AAV) over 5 years, necessitating long-term treatment. Although there have been studies looking at predictors of relapse in AAV, this research has yet to translate clinically into guidance on tailored therapy. The aim of this systematic review was to identify and meta-analyse existing risk factors from the literature and produce a model to calculate individualised patient risk of relapse. METHOD: A search strategy was developed to include all studies identifying predictors of AAV relapse using multivariate analysis. Individual risk factors were extracted and pooled hazard ratios (HRs) calculated. A model to predict the time to first relapse based on identified risk factors was tested retrospectively using a cohort of patients with AAV. RESULTS: The review of 2674 abstracts identified 117 papers for full text review, with 16 eligible for inclusion. Pooled HRs were calculated from significant risk factors, including anti-PR3 ANCA positivity [HR 1.69 (95% CI 1.46, 1.94)], cardiovascular involvement [HR 1.78 (95% CI 1.26, 2.53)], creatinine >200 µmol/l (relative to creatinine ≤100) [HR 0.39 (95% CI 0.22, 0.69)] and creatinine 101-200 µmol/l [HR 0.81 (95% CI 0.77, 0.85)]. Using data from 182 AAV patients to validate the model gave a C-statistic of 0.61. CONCLUSION: Anti-PR3 ANCA positivity, lower serum creatinine and cardiovascular system involvement are all associated with an increased risk of relapse, and a combination of these risk factors can be used to predict the individualised risk of relapse. In order to produce a clinically useful model to stratify risk, we need to identify more risk factors, with a focus on robust biomarkers.

The Longitudinal Course of Fatigue in Antineutrophil Cytoplasmic Antibody-associated Vasculitis.

OBJECTIVE: Fatigue is common and burdensome in antineutrophil cytoplasmic antibody-associated vasculitis (AAV). This study aimed to understand how fatigue changes over time following treatment initiation and to determine whether individuals with the poorest prognosis can be robustly identified. METHODS: One hundred forty-nine patients with AAV and new-onset disease recruited to 2 clinical trials (RITUXVAS and MYCYC) were followed for 18 months. Fatigue was measured at baseline and 6-month intervals using the vitality domain of the Medical Outcomes Study Short Form-36 quality of life questionnaire and compared to a cohort of 470 controls. Group-based trajectory modeling (GBTM) determined trajectories of the symptom to which baseline characteristics and ongoing fatigue scores were compared. RESULTS: Fatigue levels at diagnosis were worse in patients than controls [median (interquartile range; IQR) 30 (10-48) vs 70 (55-80); p < 0.001], with 46% of patients reporting severe fatigue. Fatigue improved after 6 months of treatment but remained worse than in controls (p < 0.001). GBTM revealed varied trajectories of fatigue: low fatigue stable (n = 23), moderate baseline fatigue improvers (n = 29), high baseline fatigue improvers (n = 61), and stable baseline high fatigue (n = 37). Participants who followed stable high fatigue trajectories had lower vasculitis activity compared to improvers, but no other demographic or clinical variables differed. CONCLUSION: This study longitudinally measured fatigue levels in patients with AAV. Although most patients improved following treatment, an important subgroup of patients reported persistently high levels of fatigue that did not change. Few clinical or laboratory markers distinguished these patients, suggesting alternative interventions specific for fatigue are required. [clinicaltrialsregister.eu, RITUXVAS EudraCT number: 2005-003610-15; MYCYC EudraCT number: 2006-001663-33].

Predictors of fatigue in rheumatoid arthritis.

People with RA commonly experience fatigue. Fatigue is a key contributor to increased clinical care costs, primary care consultations and employment loss. Despite this, our understanding of the prognostic of factors of poor fatigue outcomes is lacking and fatigue is poorly managed. Examining longitudinal predictors of fatigue can identify both individuals 'at risk' of poor prognosis, and candidate mechanisms that are worthy of greater inspection. This review discusses the factors most commonly investigated as being implicated in the prognosis of RA fatigue. The available data appears to implicate generic factors such as pain, mental health, disability and sleep as consistent predictors of fatigue outcome, while the role of disease activity and inflammation seems less clear. However, the existing data are not without methodological limitations and there have been no specific studies primarily designed to investigate the inflammatory biomarkers of fatigue. Future studies are required to more comprehensively and robustly determine the mechanisms of fatigue.

Maximizing Engagement in Mobile Health Studies: Lessons Learned and Future Directions.

The widespread availability of smartphones, tablets, and smartwatches has led to exponential growth in the number of mobile health (mHealth) studies conducted. Although promising, the key challenge of all apps (both for research and nonresearch) is the high attrition rate of participants and users. Numerous factors have been identified as potentially influencing engagement, and it is important that researchers consider these and how best to overcome them within their studies. This article discusses lessons learned from attempting to maximize engagement in 2 successful UK mHealth studies-Cloudy with a Chance of Pain and Quality of Life, Sleep and Rheumatoid Arthritis.

Differences in long-term physical activity trajectories among individuals with chronic widespread pain: A secondary analysis of a randomized controlled trial.

BACKGROUND: Little is known about long-term physical activity (PA) maintenance in those with chronic widespread pain (CWP) following an exercise intervention. This study examined PA over time to identify the existence and characteristics of subgroups following distinct PA trajectories. METHODS: Data come from individuals with CWP who took part in a 2 × 2 factorial randomized controlled trial, receiving either exercise or both exercise and cognitive behavioural therapy treatment. Information, including self-report PA, was collected at baseline recruitment, immediately post-intervention, 3, 24 and 60+ month post-treatment. Analyses were conducted on 196 men and women with ≥ 3 PA data points. Group-based trajectory modelling was used to identify latent PA trajectory groups and baseline characteristics (e.g., demographics, pain, self-rated health, fatigue, coping-strategy use and kinesiophobia) of these groups. RESULTS: The best fitting model identified was one with three trajectories: "non-engagers" (n = 32), "maintainers" (n = 144) and "super-maintainers" (n = 20). Overall, mean baseline PA levels were significantly different between groups (non-engagers: 1.1; maintainers: 4.6; super-maintainers: 8.6, p < 0.001) and all other follow-up points. Non-engagers reported, on average, greater BMI, higher disabling chronic pain, poorer self-rated health, physical functioning, as well as greater use of passive coping strategies and lower use of active coping strategies. CONCLUSIONS: The majority of individuals with CWP receiving exercise as part of a trial were identified as long-term PA maintainers. Participants with poorer physical health and coping response to symptoms were identified as non-engagers. For optimal symptom management, a stratified approach may enhance initiation and long-term PA maintenance in individuals with CWP. SIGNIFICANCE: Chronic pain can be a major barrier to engaging in exercise, a popular self-management strategy. Our findings identify three distinct long-term physical activity trajectories for individuals receiving the same exercise intervention. This suggests an approach by health care providers which identifies individuals who would benefit from additional support to enhance initiation and long-term physical activity maintenance could deliver better outcomes for such patients.

Central sensitization predicts greater fatigue independently of musculoskeletal pain.

OBJECTIVES: To test whether central sensitization was associated with greater fatigue, independently of musculoskeletal pain. METHODS: 2477 prospective cohort study participants completed a baseline questionnaire comprising the Chalder Fatigue Scale (CFQ), pain, demographics, physical activity, anxiety, depression and medication use. In a clinical assessment of 290 (11.7%) participants, central sensitization was measured by the wind-up ratio test at the hand (WUR-H) and foot (WUR-F). Bioelectric impedance determined proportion body fat. All participants were followed up 12 months later, at which time they completed the CFQ. Linear regression, with inverse probability sampling weights, tested the relationship between WUR at baseline and CFQ at 12 months, adjusted for baseline CFQ, demographics, lifestyle factors, mental health and baseline pain. RESULTS: At baseline, the median interquartile range WUR-H and WUR-F were similar (2.3 (1.5, 4.0) and 2.4 (1.6, 3.9) respectively) and did not differ by sex (difference WUR-H: -0.29, 95% confidence interval -1.28-0.71; WUR-F: -0.57 (-1.50-0.36) or age(WUR-H: -0.53, -1.49-0.43; WUR-F:-0.08, -0.98-0.82). WUR-H scores (ß = 0.11, 95% confidence interval: 0.07-0.16) and WUR-F scores (0.13, 0.08-0.17) were positively associated with CFQ scores at follow-up, independently of baseline CFQ and other covariates. These associations were not explained by baseline pain. CONCLUSION: Fatigue was predicted by central sensitization, independently of the presence of pain. For those seeking to treat fatigue, the benefit of interventions that reduce central sensitization should be investigated.

Sleep and Pain: A Systematic Review of Studies of Mediation.

OBJECTIVES: A relationship between sleep and pain is well established. A better understanding of the mechanisms that link sleep and pain intensity is urgently needed to optimize pain management interventions. The objective of this systematic review was to identify, synthesize, and critically appraise studies that have investigated putative mediators on the path between sleep and pain intensity. METHODS: A systematic search of 5 electronic bibliographic databases (EMBASE, MEDLINE, CINAHL, PsycINFO, and the Cochrane Central Register of Controlled Trials) was conducted. Eligible studies had to apply a formal test of mediation to variables on the path between a sleep variable and pain intensity or vice versa. All searches, data extraction and quality assessment were conducted by at least 2 independent reviewers. RESULTS: The search yielded 2839 unique articles, 9 of which were eligible. Of 13 mediation analyses, 11 investigated pathways from a sleep variable to pain intensity. Putative mediators included affect/mood, depression and/or anxiety, attention to pain, pain helplessness, stress, fatigue, and physical activity. Two analyses investigated pathways from pain intensity to a sleep variable, examining the potentially mediating role of depressive symptoms and mood. Although evidence supported a mediating role for psychological and physiological aspects of emotional experiences and attentional processes, methodological limitations were common, including use of cross-sectional data and minimal adjustment for potential confounders. DISCUSSION: A growing body of research is applying mediation analysis to elucidate mechanistic pathways between sleep and pain intensity. Currently sparse evidence would be illuminated by more intensively collected longitudinal data and improvements in analysis.

Fatigue independently predicts different work disability dimensions in etanercept-treated rheumatoid arthritis and ankylosing spondylitis patients.

BACKGROUND: Work disability remains a significant problem in ankylosing spondylitis (AS) and rheumatoid arthritis (RA), despite biological therapy. This study aimed to test the hypothesis that the prevalent symptom of fatigue longitudinally predicts work disability among RA and AS patients commencing etanercept. METHODS: Two observational studies, comprising RA and AS etanercept commencers, respectively, were analysed. Both provided data on work disability over 1 year and a comprehensive set of putative predictors, including fatigue. A series of repeated measures models were conducted, including baseline variables, visit (6/12 months), and the interaction between visit and each of the explanatory variables. RESULTS: A total of 1003 AS and 1747 RA patients were assessed. For AS, fatigue was significantly associated with presenteeism (linear mixed model coefficient 3.75, 95% confidence interval (CI) 2.14 to 5.36) and activity impairment (2.62, 1.26 to 3.98), but not with work productivity loss (1.81, -0.40 to 4.02) or absenteeism (generalised linear mixed model odds ratio (OR) 1.18, 95% CI 0.92 to 1.51). In RA, fatigue was associated with presenteeism (coefficient 3.44, 95% CI 2.17 to 4.70), activity impairment (1.52, 0.79 to 2.26), work productivity loss (4.16, 2.47 to 5.85), and absenteeism (OR 1.23, 95% CI 1.02 to 1.49). The lack of significant interactions between fatigue and visit supported a consistent effect of baseline fatigue over time. CONCLUSIONS: Among patients beginning etanercept therapy, fatigue has a significant and independent effect on absenteeism, presenteeism, productivity loss, and activity impairment for RA patients and a significant but dimension-selective effect on work disability among AS patients. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00544557 . Registered on 16 October 2007. ClinicalTrials.gov, NCT00488475 . Registered on 20 June 2006.

Quality of life, sleep and rheumatoid arthritis (QUASAR): a protocol for a prospective UK mHealth study to investigate the relationship between sleep and quality of life in adults with rheumatoid arthritis.

INTRODUCTION: People with rheumatoid arthritis (RA) frequently report reduced health-related quality of life (HRQoL), the impact one's health has on physical, emotional and social well-being. There are likely numerous causes for poor HRQoL, but people with RA have identified sleep disturbances as a key contributor to their well-being. This study will identify sleep/wake rhythm-associated parameters that predict HRQoL in patients with RA. METHODS AND ANALYSIS: This prospective cohort study will recruit 350 people with RA, aged 18 years or older. Following completion of a paper-based baseline questionnaire, participants will record data on 10 symptoms including pain, fatigue and mood two times a day for 30 days using a study-specific mobile application (app). A triaxial accelerometer will continuously record daytime activity and estimate evening sleep parameters over the 30 days. Every 10 days following study initiation, participants will complete a questionnaire that measures disease specific (Arthritis Impact Measurement Scale 2-Short Form (AIMS2-SF)) and generic (WHOQOL-BREF) quality of life. A final questionnaire will be completed at 60 days after entering the study. The primary outcomes are the AIMS2-SF and WHOQOL-BREF. Structural equation modelling and latent trajectory models will be used to examine the relationship between sleep/wake rhythm-associated parameters and HRQoL, over time. ETHICS AND DISSEMINATION: Results from this study will be disseminated at regional and international conferences, in peer-reviewed journals and Patient and Public Engagement events, as appropriate.

Recruitment and Ongoing Engagement in a UK Smartphone Study Examining the Association Between Weather and Pain: Cohort Study.

BACKGROUND: The huge increase in smartphone use heralds an enormous opportunity for epidemiology research, but there is limited evidence regarding long-term engagement and attrition in mobile health (mHealth) studies. OBJECTIVE: The objective of this study was to examine how representative the Cloudy with a Chance of Pain study population is of wider chronic-pain populations and to explore patterns of engagement among participants during the first 6 months of the study. METHODS: Participants in the United Kingdom who had chronic pain (≥3 months) and enrolled between January 20, 2016 and January 29, 2016 were eligible if they were aged ≥17 years and used the study app to report any of 10 pain-related symptoms during the study period. Participant characteristics were compared with data from the Health Survey for England (HSE) 2011. Distinct clusters of engagement over time were determined using first-order hidden Markov models, and participant characteristics were compared between the clusters. RESULTS: Compared with the data from the HSE, our sample comprised a higher proportion of women (80.51%, 5129/6370 vs 55.61%, 4782/8599) and fewer persons at the extremes of age (16-34 and 75+). Four clusters of engagement were identified: high (13.60%, 865/6370), moderate (21.76%, 1384/6370), low (39.35%, 2503/6370), and tourists (25.44%, 1618/6370), between which median days of data entry ranged from 1 (interquartile range; IQR: 1-1; tourist) to 149 (124-163; high). Those in the high-engagement cluster were typically older, whereas those in the tourist cluster were mostly male. Few other differences distinguished the clusters. CONCLUSIONS: Cloudy with a Chance of Pain demonstrates a rapid and successful recruitment of a large, representative, and engaged sample of people with chronic pain and provides strong evidence to suggest that smartphones could provide a viable alternative to traditional data collection methods.

Mortality in patients with interstitial lung disease treated with rituximab or TNFi as a first biologic.

OBJECTIVES: Guidelines cautioned prescribing of tumour necrosis factor inhibitors (TNFi) to patients with rheumatoid arthritis and interstitial lung disease (RA-ILD) after reports of new or worsening of ILD. Less is known about outcomes among patients with RA-ILD who receive rituximab (RTX). This study compares mortality in patients with RA-ILD who received RTX or TNFi as their first biologic. METHODS: Participants with RA-ILD recruited to the British Society for Rheumatology Biologics Register for RA were included. Death rates were calculated and risk comparisons were made using Cox regression. Causes of death, including the frequency in which ILD was recorded on death certificates were examined. RESULTS: 43 patients on RTX and 309 on TNFi were included. RTX recipients had shorter disease duration and less disability. Death rates were 94.8 (95%CI: 74.4 to 118.7) and 53.0 (22.9 to 104.6) per 1000 person years, respectively. The adjusted mortality risk was halved in the RTX cohort, but the difference was not statistically significant (HR 0.53, 95% CI: 0.26 to 1.10). ILD was the underlying cause of death in 1 of 7 RTX deaths (14%) and 12 of 76 TNFi deaths (16%). CONCLUSIONS: Patients with RA-ILD who received RTX had lower mortality rates compared to TNFi. The absence of information on ILD severity or subtype prevents conclusions of which drug represents the best choice in patients with RA-ILD and active arthritis.

Identification and Validation of Clinically Relevant Clusters of Severe Fatigue in Rheumatoid Arthritis.

OBJECTIVE: The considerable heterogeneity of rheumatoid arthritis (RA)-related fatigue is the greatest challenge to determining pathogenesis. The identification of homogenous subtypes of severe fatigue would inform the design and analysis of experiments seeking to characterize the likely numerous causal pathways that underpin the symptom. This study aimed to identify and validate such fatigue subtypes in patients with RA. METHODS: Data were obtained from patients recruited to the British Society for Rheumatology Biologics register for RA, as either receiving traditional disease-modifying antirheumatic drugs (DMARD cohort, n = 522) or commencing anti-tumor necrosis factor therapy (anti-TNF cohort, n = 3909). In those reporting severe fatigue (Short-Form 36 vitality ≤ 12.5), this cross-sectional analysis applied hierarchical clustering with weighted-average linkage identified clusters of pain, fatigue, mental health (all Short-Form 36), disability (Health Assessment Questionnaire), and inflammation (erythrocyte sedimentation rate) in the DMARD cohort. K-means clustering sought to validate the solution in the anti-TNF cohort. Clusters were characterized using a priori generated symptom definitions and between-cluster comparisons. RESULTS: Four severe fatigue clusters, labeled as basic (46%), affective (40%), inflammatory (4.5%), and global (8.9%) were identified in the DMARD cohort. All clusters had severe levels of pain and disability and were distinguished by the presence/absence of poor mental health and high inflammation. The same symptom clusters were present in the anti-TNF cohort, although the proportion of participants in each cluster differed (basic = 28.7%; affective = 30.2%; global = 24.1%; inflammatory = 16.9%). CONCLUSIONS: Among RA patients with severe fatigue, recruited to two diverse RA cohorts, clinically relevant clusters were identified and validated. These may provide the basis for future mechanistic studies and ultimately support a stratified approach to fatigue management.

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.

OBJECTIVES: RA-related fatigue is common and debilitating, but does not always respond to immunotherapy. In the context of anti-TNF therapy, we aimed to examine whether patients achieving disease remission experienced remission of fatigue. METHODS: Data from the British Society for Rheumatology Biologics Register for RA were used. In participants with severe baseline fatigue [36-item Short Form Health Survey (SF-36) vitality score ⩽12.5], we identified those in disease remission [28-joint DAS (DAS28) <2.6] by 6 months. Fatigue response was evaluated according to partial (SF-36 vitality score >12.5) and complete remission (SF-36 vitality score >50) at follow-up. Demographic (e.g. sex, age), clinical (e.g. inflammation, joint erosion and co-morbidities) and psychosocial (e.g. SF-36 domains and HAQ) characteristics were compared between responder and non-responder groups. RESULTS: Severe baseline fatigue was reported by 2652 participants, of whom 271 (10%) achieved a DAS28 <2.6 by 6 months. In total, 225 participants (83%) reported partial remission and were distinguished from those who did not by better health status on all psychosocial domains. Far fewer [n = 101 (37.3%)] reported full fatigue remission. In addition to reporting clinically poorer health status, they were distinguished on the basis of a history of hypertension, depression and stroke as well as baseline treatment use of steroids and antidepressants. CONCLUSION: Despite achieving clinical remission, many RA patients do not achieve complete remission of their fatigue. Therefore, despite being important in overall disease control, reductions in disease activity are not always sufficient to ameliorate fatigue, so other symptom-specific management approaches must be considered for those for whom fatigue does not resolve.

Examining Changes in Central and Peripheral Pain as Mediates of Fatigue Improvement: Results From the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis.

OBJECTIVE: Following anti-tumor necrosis factor (anti-TNF) therapy, improvements in rheumatoid arthritis (RA) fatigue are driven by reductions in pain. However, therapies may modify both central and peripheral pain. This study sought to examine the hypothesis that reductions in fatigue after anti-TNF therapy reflect changes in central, not peripheral, pain mechanisms. METHODS: Data came from patients with severe baseline fatigue (Short Form 36 health survey [SF-36] vitality scale ≤12.5; n = 2,652), recruited to the British Society for Rheumatology Biologics Register for RA for commencing anti-TNF therapies between October 2000 and November 2008. Data of interest comprised change over 6 months in fatigue, pain (SF-36 bodily pain scale), and disease activity constituents (Disease Activity Score in 28 joints, erythrocyte sedimentation rate [ESR], global health, swollen joints, and tender joints). Principal components factor analysis with varimax rotation determined latent variables of symptom change; variables were accepted provided they had eigenvalues ≥1. RESULTS: Six factors were identified, of which 2 met acceptance criteria (eigenvalues of 2.39 and 1.14, respectively). Following rotation, loadings indicated that factor 1 comprised markers of peripheral inflammation: change in ESR, swollen joints, tender joints, and global health. This distinct loading led to factor 1 being labeled peripheral inflammation. Conversely, factor 2 comprised change in pain, fatigue, and global health and an absence of peripheral inflammation markers and was therefore labeled central inflammation. CONCLUSION: Following anti-TNF therapies, reductions in fatigue and pain appear to reflect improvements in central, rather than peripheral, inflammation. Therefore, for those seeking to treat fatigue via pain mechanisms, improvements may be maximized by the application of treatment modalities that effectively target central mechanisms.