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Objective: To investigate how social support, financial status, and lifestyle influence the development of excess disability in rheumatoid arthritis (RA). Methods: Data were obtained from the Étude et Suivi des Polyarthrites Indifférenciées Récentes (ESPOIR) cohort study of people with RA. A previous analysis identified groups with similar inflammation trajectories but markedly different disability over 10 years; those in the higher disability trajectory groups were defined as having “excess disability.” Self-reported data regarding contextual factors (social support, financial situation, lifestyle) were obtained from participants, and they completed patient-reported outcome measures (pain, fatigue, anxiety, depression) at baseline. The direct effect of the contextual factors on excess disability and the effect mediated by patient-reported outcome measures were assessed using structural equation models. Findings were validated in 2 independent data sets (Norfolk Arthritis Register [NOAR], Early Rheumatoid Arthritis Network [ERAN]). Results: Of 538 included ESPOIR participants (mean age ± SD 48.3 ± 12.2 years; 79.2% women), 200 participants (37.2%) were in the excess disability group. Less social support (β = 0.17 [95% confidence interval (95% CI) 0.08, 0.26]), worse financial situation (β = 0.24 [95% CI 0.14, 0.34]), less exercise (β = 0.17 [95% CI 0.09–0.25]), and less education (β = 0.15 [95% CI 0.06, 0.23]) were associated with excess disability group membership; smoking, alcohol consumption, and body mass index were not. Fatigue and depression mediated a small proportion of these effects. Similar results were seen in NOAR and ERAN. Conclusion: Greater emphasis is needed on the economic and social contexts of individuals with RA at presentation; these factors might influence disability over the following decade.

Background Tumour necrosis factor-alpha inhibitors (TNFi) have revolutionized the treatment of moderate-to-severe psoriasis. Following patent expiry of the originator biologics, TNFi biosimilars became available, presenting the opportunity for significant reductions in drug costs. Objectives To describe the uptake of TNFi biosimilars for psoriasis treatment in the UK and Ireland. Methods This observational cohort study utilizes data from the British Association of Dermatologists Biologic and Immunomodulators Register (BADBIR), a national pharmacovigilance study register for patients with psoriasis on systemic treatments. We analysed biosimilar uptake trends over time in nine geographical regions of England along with Wales, Scotland, Northern Ireland and the Republic of Ireland. We assessed the incidence of switching to biosimilars in an originator-user cohort (switchers). Patients on originators infliximab, etanercept and adalimumab at the time originator patents expired, entered the cohort on 1 February 2015, August 2015 and October 2018, respectively, and were followed up until 31 October 2021. Trends in biosimilar initiations were assessed in an adalimumab-naïve cohort who started adalimumab between 1 October 2018 and 31 July 2019 (starters). We assessed the associations between patient factors and originator-to-biosimilar switching and biosimilar initiation using a multivariable Cox regression model and a multivariable logistic regression model, respectively. Results Included in the originator-user cohort were 4202 patients (209 on infliximab, 742 on etanercept and 3251 on adalimumab). For infliximab, etanercept and adalimumab, respectively, the cumulative incidence of originator-to-biosimilar switching increased with time to 14.8%, 23.6% and 66.6% after 3 years. Across geographical regions, 3-year switching rates varied from 0% to 43.7% for infliximab; from 0% to 40.4% for etanercept; and from 12.5% to 84.3% for adalimumab. Out of the 528 patients included in the adalimumab-naïve cohort, 67.8% started on biosimilars. Originator-to-biosimilar switching and biosimilar initiation were more common in men and in patients who had lower Psoriasis Area and Severity Index at cohort entry. Conclusions The uptake of biosimilars increased over time and varied considerably across the UK and Ireland; adalimumab had the highest biosimilar uptake rate compared with that of other TNFi drugs.

Background/Aims Interleukin 6 inhibitors (IL-6i) can increase LDL cholesterol levels, which raises concerns about the risk of myocardial infarction (MI) in patients with rheumatoid arthritis (RA) receiving this therapy. This study aims to compare the risk of MI between people with RA in the UK clinical setting receiving IL-6i or tumour necrosis factor inhibitors (TNFi) overall or by line of therapy (LoT). Methods Patients with RA registered between 01/10/2001 and 27/05/2022 with BSRBR-RA starting IL-6i or TNFi treatments were included. Occurrence of MI was identified from clinical follow-up forms and through cause of death reported by the national UK death register. Only those MIs occurring whilst the patient was actively receiving drug were included. The risk of MI in patients receiving IL6i compared to TNFi was compared using Cox regression, adjusted for baseline co-variates using propensity scores (PS, see Table 1). Follow-up commenced at the start of the drug of interest and patients were censored at occurrence of MI, death, discontinuation of therapy or last follow-up visit, whichever came first. Multiple imputation was used for missing data. To account for known differences in LoT use of TNFi and IL6i (with IL6i more likely as a later line bDMARD), overall analyses adjusted for LoT in PS and secondary analyses by LoT were conducted. Direct switches between originator to biosimilars were considered the same treatment. Results A total of 29,596 IL6i or TNFi treatments in 20,725 patients were included (3,098 IL-6i; 26,498 TNFi), representing 153,913 person-years of exposure. Compared to patients receiving TNFi, patients starting IL-6i treatment were older, had longer disease duration, less likely to use methotrexate and steroids, and had more comorbidities. During follow-up, 372 MIs occurred, 27 on IL-6i and 345 on TNFi, with an overall lower crude rate of MI in patients receiving IL6i compared to TNFi. After PS adjustment, the risk of MI was not significantly different between the two treatment overall (HR 0.77, 95% CI 0.48-1.24) or when stratified by LoT (Table 1). Conclusion This study could not identify any difference in risk of MI between IL-6i and TNFi treatment after patient characteristics and LoT were considered. Disclosure Z. Tian: None. L. Kearsley-Fleet: None. K. Lauper: Honoraria; Celltrion, Pfizer, Viatris, Galapagos. S. Haughton: None. K. Watson: None. M. Lunt: None. J. Mclaughlin: None. A. Verma: None. K.L. Hyrich: Honoraria; Abbvie. Grants/research support; Pfizer, BMS.

Background/Aims Rheumatic and musculoskeletal diseases (RMDs) are some of the most common indications for prescribed opioids. It is unclear how opioid prescribing has changed in the UK for RMDs, especially during the COVID-19 pandemic with limited healthcare access and cancelled elective-surgical interventions, which could impact prescribing in either direction. We aimed to investigate trends in opioid prescribing in RMDs and assess the impact of the pandemic in the UK. Methods Adult patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), axial spondyloarthritis (AxSpA), systemic lupus erythematosus (SLE), osteoarthritis (OA) and fibromyalgia with opioid prescriptions between 01/Jan/2006–31/Aug/2021 without prior cancer in the UK Clinical Practice Research Datalink (CPRD) were included. We calculated age- and gender-standardised yearly rates of people with opioid prescriptions between 2006–2021, and identified change points in trends by checking whether the rate of change of standardised rates crossed zero. For people with opioid prescriptions, monthly measures of mean morphine milligram equivalents (MME)/day were calculated between 2006–2021. To assess the impact of the pandemic, we fitted regression models to the monthly number of people with opioid prescriptions between Jan/2015–Aug/2021. The time coefficient reflects the trend pre-pandemic and the interaction term coefficient represents the change in the trend during the pandemic. Results We included 1,313,519 patients: 36,932 with RA, 12,649 with PsA, 6,811 with AxSpA, 6,423 with SLE, 1,255,999 with OA, and 66,944 with fibromyalgia. People with opioid prescriptions increased from 2006 to 2018 for OA, to 2019 for RA, AxSpA and SLE, to 2020 for PsA, and to 2021 for fibromyalgia, and all plateaued/decreased afterwards. OA patients on opioids increased from 466.8/10,000 persons in 2006 to a peak of 703.0 in 2018, followed by a decline to 575.3 in 2021. From 2006 to 2021, there was a 4.5-fold increase in fibromyalgia opioid users (17.7 vs.78.5/10,000 persons). In this period, MME/day increased for all RMDs, with the highest for fibromyalgia (≥35). During COVID-19 lockdowns, RA, PsA and fibromyalgia showed significant changes in the trend of people with opioid prescriptions. With a decreasing trend for RA (-0.001,95%CI=-0.002,-0.001) and a decreasing-to-flat curve for PsA (0.0010,95%CI=0.0006,0.0015) pre-pandemic until Feb/2020, the trends changed by -0.005 (95%CI=-0.008,-0.002) for RA and -0.003 (95%CI=-0.006,-0.0003) for PsA, leading to steeper decreasing trends during the pandemic (Mar/2020–Aug/2021). Fibromyalgia, conversely, had an increasing trend (0.009,95%CI=0.008,0.009) pre-pandemic, and this trend started decreasing by -0.009 (95%CI=-0.011,-0.006) during the pandemic. Conclusion The plateauing/decreasing trend of people with opioid prescriptions in RMDs after 2018 may reflect the efforts to tackle the rising opioid prescribing in UK primary care. Of all RMDs, fibromyalgia patients had the highest MME/day throughout the study period. COVID-19 lockdowns contribute to fewer people on opioids for most RMDs, reassuring there was no sudden increase in opioid prescribing during the pandemic. Disclosure Y. Huang: None. D.A. Jenkins: None. B.B. Yimer: None. J. Benitez-Aurioles: None. N. Peek: None. M. Lunt: None. W.G. Dixon: Consultancies; WGD has received consultancy fees from Google unrelated to this work. M. Jani: None.

Aims The aim of this study was to determine if uncemented acetabular polyethylene (PE) liner geometry, and lip size, influenced the risk of revision for instability or loosening. Methods A total of 202,511 primary total hip arthroplasties (THAs) with uncemented acetabular components were identified from the National Joint Registry (NJR) dataset between 2003 and 2017. The effect of liner geometry on the risk of revision for instability or loosening was investigated using competing risk regression analyses adjusting for age, sex, American Society of Anesthesiologists grade, indication, side, institution type, surgeon grade, surgical approach, head size, and polyethylene crosslinking. Stratified analyses by surgical approach were performed, including pairwise comparisons of liner geometries. Results The distribution of liner geometries were neutral (39.4%; 79,822), 10° (34.5%; 69,894), 15° (21.6%; 43,722), offset reorientating (2.8%; 5705), offset neutral (0.9%; 1,767), and 20° (0.8%; 1,601). There were 690 (0.34%) revisions for instability. Compared to neutral liners, the adjusted subhazard ratios of revision for instability were: 10°, 0.64 (p < 0.001); 15°, 0.48 (p < 0.001); and offset reorientating, 1.6 (p = 0.010). No association was found with other geometries. 10° and 15° liners had a time-dependent lower risk of revision for instability within the first 1.2 years. In posterior approaches, 10° and 15° liners had a lower risk of revision for instability, with no significant difference between them. The protective effect of lipped over neutral liners was not observed in laterally approached THAs. There were 604 (0.3%) revisions for loosening, but no association between liner geometry and revision for loosening was found. Conclusion This registry-based study confirms a lower risk of revision for instability in posterior approach THAs with 10° or 15° lipped liners compared to neutral liners, but no significant difference between these lip sizes. A higher revision risk is seen with offset reorientating liners. The benefit of lipped geometries against revision for instability was not seen in laterally approached THAs. Liner geometry does not seem to influence the risk of revision for loosening. Cite this article: Bone Joint J 2021;103-B(12):1774–1782.

Objectives Burden of comorbidities are largely unknown in JIA. From 2000, national and international patient registries were established to monitor biologic treatment, disease activity and adverse events in patients with JIA. The aim of this analysis was to investigate in parallel, for the first time, three of the largest JIA registries in Europe/internationally—UK JIA Biologic Registers (BCRD/BSPAR-ETN), German biologic registers (BiKeR/JuMBO), multinational Pharmachild—to quantify the occurrence of selected comorbidities in patients with JIA. Methods Information on which data the registers collect were compared. Patient characteristics and levels of comorbidity were presented, focussing on four key conditions: uveitis, MAS, varicella, and history of tuberculosis. Incidence rates of these on MTX/biologic therapy were determined. Results 8066 patients were registered into the three JIA registers with similar history of the four comorbidities across the studies; however, varicella vaccination coverage was higher in Germany (56%) vs UK/Pharmachild (16%/13%). At final follow-up, prevalence of varicella infection was lower in Germany (15%) vs UK/Pharmachild (37%/50%). Prevalence of TB (0.1–1.8%) and uveitis (15–19%) was similar across all registers. The proportion of systemic-JIA patients who ever had MAS was lower in Germany (6%) vs UK (15%) and Pharmachild (17%). Conclusion This analysis is the first and largest to investigate the occurrence of four important comorbidities in three JIA registries in Europe and the role of anti-rheumatic drugs. Combined, these three registries represent one of the biggest collection of cases of JIA worldwide and offer a unique setting for future JIA outcome studies.

Aim to determine the impact of frailty on patient-reported outcomes following hip and knee arthroplasty. Methods we used linked primary and secondary care electronic health records. Frailty was assessed using the electronic frailty index (categorised: fit, mild, moderate, severe frailty). We determined the association between frailty category and post-operative Oxford hip/knee score (OHS/OKS) using Tobit regression. We calculated the proportion of patients in each frailty category who achieved the minimally important change (MIC) in OHS (≥8 points) and OKS (≥7 points) and the proportion who reported a successful outcome (hip/knee problems either ‘much better’ or ‘a little better’ following surgery). Results About 42,512 people who had a hip arthroplasty and 49,208 who had a knee arthroplasty contributed data. In a Tobit model adjusted for pre-operative OHS/OKS, age, sex and quintile of index of multiple deprivation, increasing frailty was associated with decreasing post-operative OHS and OKS, respectively, β-coefficient (95% CI) in severely frail versus fit, −6.97 (−7.44, −6.49) and − 5.88 (−6.28, −5.47). The proportion of people who achieved the MIC in OHS and OKS, respectively, decreased from 92 and 86% among fit individuals to 84 and 78% among those with severe frailty. Patient-reported success following hip and knee arthroplasty, respectively, decreased from 97 and 93% among fit individuals to 90 and 83% among those with severe frailty. Conclusion frailty adversely impacts on patient-reported outcomes following hip and knee arthroplasty. However, even among those with severe frailty, the large majority achieved the MIC in OHS/OKS and reported a successful outcome.

Objectives To describe how many people with RA reduce their baseline physical activity level over the first year of MTX treatment, and which factors predict this. Methods Data came from the Rheumatoid Arthritis Medication Study (RAMS), a prospective cohort of people with early RA starting MTX. Participants reported demographics and completed questionnaires at baseline, and 6 and 12 months, including reporting the number of days per week they performed ≥20 min of physical activity, coded as none, low (1–3 days) or high (4–7 days). The physical activity levels of participants over 12 months are described. Predictors of stopping physical activity were assessed using multivariable logistic regression. Results In total, 1468 participants were included [median (interquartile range) age 60 (50, 69) years; 957 (65.2%) women]. At baseline, the physical activity levels of the people with RA were: none = 408 (27.8%), low = 518 (35.3%) and high = 542 (36.9%). Eighty percent of participants maintained some physical activity or began physical activity between assessments (baseline to 6 months = 79.3%, 6 months to 12 months = 80.7%). In total, 24.1% of participants reduced physical activity and 11.3% of participants stopped performing physical activity between baseline and 6 months (6 months to 12 months: 22.6% and 10.2%, respectively). Baseline smoking, higher disability and greater socioeconomic deprivation were associated with stopping physical activity. Conclusion Many people with early RA were not performing physical activity when starting MTX, or stopped performing physical activity over the first year of treatment. These people may require interventions to stay active. These interventions need to be mindful of socioeconomic barriers to physical activity participation.

Confounding can cause substantial bias in nonexperimental studies that aim to estimate causal effects. Propensity score methods allow researchers to reduce bias from measured confounding by summarizing the distributions of many measured confounders in a single score based on the probability of receiving treatment. This score can then be used to mitigate imbalances in the distributions of these measured confounders between those who received the treatment of interest and those in the comparator population, resulting in less biased treatment effect estimates. This methodology was formalized by Rosenbaum and Rubin in 1983 and, since then, has been used increasingly often across a wide variety of scientific disciplines. In this review article, we provide an overview of propensity scores in the context of real-world evidence generation with a focus on their use in the setting of single treatment decisions, that is, choosing between two therapeutic options. We describe five aspects of propensity score analysis: alignment with the potential outcomes framework, implications for study design, estimation procedures, implementation options, and reporting. We add context to these concepts by highlighting how the types of comparator used, the implementation method, and balance assessment techniques have changed over time. Finally, we discuss evolving applications of propensity scores.

Objectives To describe the illness perceptions of patients with RA over the first year of MTX treatment, and the association between illness perceptions and outcomes. Methods Data came from the Rheumatoid Arthritis Medication Study (RAMS), a UK multicentre cohort study of RA patients starting MTX for the first time. Patients were assessed at baseline, and at 6 and 12 months. Patients completed the Brief Illness Perception Questionnaire (B-IPQ) at each assessment, as well as other patient-reported outcomes (PROs). The inflammation score (2-component DAS28) was calculated. Subgroups of patients with similar trajectories across the eight (B-IPQ) items were identified using a latent class growth model. Predictors of group membership were identified using multinomial logistic regression. Associations between subgroups and PROs over follow-up were assessed using linear mixed models. Results Three subgroups were identified in the analysis population (N = 1087): Positive illness perceptions (N = 322), Negative illness perceptions (N = 534) and Improvers (N = 231) who switched from negative to positive illness perceptions over follow-up. Baseline disability was associated with group membership [Positive vs Negative: relative risk ratio (RRR) 0.37, 95% CI: 0.25, 0.54; Improvers vs Negative: RRR 0.60, 95% CI: 0.43, 0.83], as were other PROs (pain, fatigue, anxiety, depression). The Negative group had worse disability, pain and fatigue over follow-up compared with the other groups, controlling for inflammation. Conclusion Negative illness perceptions are associated with poor PROs over time. The Improvers subgroup illustrated that illness perceptions can change in RA. Illness perceptions represent a potential therapeutic target that should be assessed using randomized trials.

Background Clinical prediction models (CPMs) predict the risk of health outcomes for individual patients. The majority of existing CPMs only harness cross-sectional patient information. Incorporating repeated measurements, such as those stored in electronic health records, into CPMs may provide an opportunity to enhance their performance. However, the number and complexity of methodological approaches available could make it difficult for researchers to explore this opportunity. Our objective was to review the literature and summarise existing approaches for harnessing repeated measurements of predictor variables in CPMs, primarily to make this field more accessible for applied researchers. Methods MEDLINE, Embase and Web of Science were searched for articles reporting the development of a multivariable CPM for individual-level prediction of future binary or time-to-event outcomes and modelling repeated measurements of at least one predictor. Information was extracted on the following: the methodology used, its specific aim, reported advantages and limitations, and software available to apply the method. Results The search revealed 217 relevant articles. Seven methodological frameworks were identified: time-dependent covariate modelling, generalised estimating equations, landmark analysis, two-stage modelling, joint-modelling, trajectory classification and machine learning. Each of these frameworks satisfies at least one of three aims: to better represent the predictor-outcome relationship over time, to infer a covariate value at a pre-specified time and to account for the effect of covariate change. Conclusions The applicability of identified methods depends on the motivation for including longitudinal information and the method’s compatibility with the clinical context and available patient data, for both model development and risk estimation in practice.

Purpose: Many clinical trials of promising interventions fail to see anticipated effects at follow-up. To avoid carrying out a full trial when the tested treatment is likely to be inefficacious, researchers may include one or more interim analyses, assessing for trial futility before the final analysis, discontinuing the trial early if interim effects are less than expected. The current approach tests whether the trial is likely to show futility, not whether the treatment is likely to be inefficacious. Treatments that show efficacy but with wide confidence bounds around efficacy estimates may be stopped inappropriately for futility. We present an alternative approach which focuses on the expected efficacy of the treatment. The approach uses “futility regions” to determine whether to stop trials of treatments that are unlikely to show a clinically important effect at interim—a stopping rule which requires interim interval estimates to lie entirely within a “stopping zone” (current approaches only require estimates to cross into the region of null/futile effects). We contrast this with extant methods, highlighting how the proposed approach focuses on a clinically relevant question, and protects against undue stopping because of imprecise estimates. For a researcher wanting to gather evidence of efficacious treatments, this is a desirable characteristic; trials with precise interim estimates of null effects should be stopped, whereas those with imprecise estimates that include useful effect magnitudes should be allowed to continue. Method: We created a simulation study, testing 1000 permutations of six different parallel-design trial scenarios, all featuring one interim analysis, and stopping only for futility. The scenarios demonstrate a range of effect sizes and variances. We implemented four types of interval-based stopping rules—using Frequentist and Bayesian approaches—and compared their performance to the more commonly used O’Brien-Fleming and Pocock designs. We used a range of stopping rules, 15 in total, to demonstrate the limits of the approaches in the different trial scenarios. Results: All approaches discriminated well between trials with a final null effect, and those with a final large treatment effect. However, when the trial variance was different to that expected at the design stage, the interval-based approaches demonstrated favorable characteristics—continuing more permutations with imprecise but promising estimates, and stopping more of those with precise estimates of clinically trivial or null (futile) effect sizes (table). Empirical Bayesian approaches showed enhanced precision compared to the other methods, due to their property of allowing interim estimates to inform the prior distributions of the final effect estimate. Conclusion: A simple implementation of adaptive trial methodology, featuring only one interim analysis and using a modified version of interval estimate stopping rules demonstrated preferable performance characteristics for the researcher seeking to stop only trials that precisely estimate null effects than more current approaches. These characteristics have the benefit of producing two possible meaningful trial endpoints: completed trials that had continued to show promise at interim, and stopped trials with precise estimates of a null effect. This contrasts with a trial which stops early with an imprecise estimate of effect, about which few conclusions can be drawn.

BACKGROUND The cardiovascular safety profile of biologic therapies used for psoriasis is unclear. OBJECTIVES To compare the risk of major cardiovascular events (CVEs; acute coronary syndrome, unstable angina, myocardial infarction and stroke) in patients with chronic plaque psoriasis treated with adalimumab, etanercept or ustekinumab in a large prospective cohort.METHODS Prospective cohort study examining the comparative risk of major CVEs was conducted using the British Association of Dermatologists Biologics and Immunomodulators Register (BADBIR). The main analysis compared adults with chronic plaque psoriasis receiving ustekinumab with tumour necrosis-α inhibitors (TNFi: etanercept and adalimumab) while the secondary analyses compared ustekinumab, etanercept, or methotrexate against adalimumab. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using overlap weights by propensity score to balance baseline covariates among comparison groups.RESULTS We included 5,468 biologic-naïve patients subsequently exposed (951 ustekinumab; 1,313 etanercept; and 3,204 adalimumab) in the main analysis. The secondary analyses also included 2,189 patients receiving methotrexate. The median (p25 - p75) follow up times for patients using ustekinumab, TNFi, adalimumab, etanercept and methotrexate were: 2.01 (1.16 - 3.21), 1.93 (1.05 - 3.34), 1.94 (1.09 - 3.32), 1.92 (0.93 - 3.45) and 1.43 (0.84 - 2.53) years, respectively. Ustekinumab, TNFi, adalimumab, etanercept and methotrexate groups had 7, 29, 23, 6 and 9 patients experiencing major CVEs, respectively. No differences in the risk of major CVEs were observed between biologic therapies (adjusted HR for ustekinumab vs TNFi: 0.96 [95%CI 0.41 - 2.22]; ustekinumab vs adalimumab: 0.81 [0.30 - 2.17]; etanercept vs adalimumab: 0.81 [0.28 - 2.30]) and methotrexate against adalimumab (1.05 [0.34 - 3.28]). CONCLUSIONS In this large prospective cohort study, we found no significant differences in the risk of major CVEs between three different biologic therapies and methotrexate. Additional studies, with longer term follow-up, are needed to investigate the potential effects of biologic therapies on incidence of major CVEs.

ObjectivesWork is an important health outcome. This study aimed to identify predictors of work loss, absenteeism and presenteeism over 1 year in RA patients commencing treatment with MTX or biologics.MethodsPatients aged 18–65 years in full/part-time employment from two UK prospective cohorts were included: MTX-starters = Rheumatoid Arthritis Medication Study; and biologic-starters = Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate. Presenteeism and absenteeism were assessed using the RA-specific Work Productivity Survey at baseline, and 6 and 12 months. Potential predictors including baseline age, gender, clinical measures (e.g. disability, pain, fatigue), psychological distress, occupation and EULAR response from baseline to 6 months were investigated.ResultsA total of 51/463 MTX-starters and 30/260 biologic-starters left work over 12 months. Higher baseline psychological distress in MTX-starters [odds ratio (OR) 1.1 (95% CI: 1.0, 1.1)] and higher disability in biologic-starters [OR 3.5 (95% CI: 1.4, 8.6)] predicted work loss. Some 16.1% of patients reported sick-leave, which was predicted by disability [OR (95% CI): MTX-starters: 1.5 (0.9, 2.3); biologic-starters: 2.4 (1.1, 5.2)]. Median presenteeism scores were very low (minimal interference) in both cohorts. Higher fatigue for MTX starters [incidence rate ratio 1.2 (95% CI: 1.0, 1.4)] and higher disability in biologic-starters (incidence rate ratio 1.4 (95% CI: 1.1, 1.7)] predicted presenteeism. Good EULAR response was associated with lower absenteeism and presenteeism in both cohorts.ConclusionPatients with RA still face significant limitations regarding their ability to work. Disability and EULAR response were the main predictors of work outcomes, emphasizing the need to control the disease and the importance of function in enabling work participation.

Background The way that GP practices organize their services impacts as much on glycaemia in type 2 diabetes as does prescribing. Aim Our aim was to evaluate the link between patients’ own perception of support within primary care and the % patients at each GP practice at target glycaemic control (TGC) and at high glycaemic risk (HGR). Design and Setting Utilisation of National Diabetes Audit (NDA) available data combined with the General practitioner patient survey (GPPS). Method The NDA 2016_17 published data on numbers of type 2 patients, levels of local diabetes services and the target glycaemic control (TGC) % and high glycaemic risk (HGR) % achieved. The GPPS 2017 published % “No” responses from long term condition (LTC) patients to the question “In the last 6 months, had you enough support from local services or organisations to help manage LTCs?”. Multivariate regression was used on the set of indicators capturing patients’ demographics and services provided. Results 6498 practices were included (with more than 2.5 million T2DM patients) and median values with band limits that included 95% practices for % “No” response to the question above was 12% (2%–30%), for TGC 67% (54%–78%) and for HGR 6% (2%–13%). The model accounted for 25% TGC variance and 26% HGR variance. The standardised β values shown as (TGC/HGR) (+=more people; −=less people) for older age (+0.24/−0.25), sulphonylurea use (−0.21/+0.14), greater social disadvantage (−0.09/+0.21), GPPS Support %No (−0.08/+0.12), %Completion 8 checks (+0.09/−0.12) and metformin use (+0.11/−0.05). Conclusion The relation between the person with diabetes and clinician in primary care is shown to be quantitatively potentially as important in influencing glycaemic outcome as the services provided and medication prescribed. We suggest that all of us in who work in the health care system can bear this in mind in our everyday work.

Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG) in terms of its overall effect on climate radiative forcing. The atmospheric residence time of methane is considerably shorter than that of carbon dioxide, but its warming potential significantly stronger. Methane is produced from natural sources such as wetlands, and as a result of human activities, such as the oil and gas industry. A small number of anomalously large anthropogenic point sources are a major contribution to the total global anthropogenic methane emission budget, thus early detection of such sources has great potential for climate mitigation.Methane satellite observations are now possible from a number of instruments with very high spatial resolution which allow to map methane emission plumes from individual emission sources. In this work, we explore the capabilities of three satellites with different specifications, spatial coverage and spatial resolutions ranging from metres (WorldView-3; multi-spectral) to tens of metres (PRISMA; hyperspectral) to kilometres (TROPOMI; hyperspectral). This leads to different capabilities for detecting and quantifying methane point sources that can complement each other. Thanks to its good coverage, TROPOMI Level 2 XCH4 data (from IUP Bremen) allows to locate areas with methane anomalies which can then be further analysed with targeted PRISMA and WorldView-3 (WV-3) observations to quantify methane emissions from small point sources.In our work, we use a fast data-driven retrieval algorithm to derive methane column enhancements from PRISMA and Worldview-3, combined with a statistical method to identify methane plumes and the well-established Integrated Mass Enhancement (IME) method to derive emission flux rates. We developed a simulation framework to characterise and test our approach. This makes use of synthetic methane plumes generated with the Large Eddy Simulation extension of the Weather Research and Forecasting model (WRF-LES) that have been embedded into WV-3 or PRISMA images. To further advance the plume detection methods and to allow automatisation, we have developed a deep learning model for WV-3 or PRISMA based on the WRF-LES simulations.In this presentation, we will describe and characterise our plume detection method for three satellite systems covering a wide range of spatial resolutions and we will introduce our deep learning approach. Both methods have been applied to case studies with a focus on emissions from coal mining in South Africa and Australia which we will use to discuss and contrast the different methods and satellite systems.

Objectives To identify groups of people with RA with different disability trajectories over 10 years, despite comparable levels of inflammation. Methods Data for this analysis came from three European prospective cohort studies of people with RA [Norfolk Arthritis Register (NOAR), Early RA Network (ERAN), Étude et Suivi des Polyarthrites Indifférenciées Récentes (ESPOIR)]. Participants were assessed regularly over 8 (ERAN) to 10 (NOAR/ESPOIR) years. Inclusion criteria were: recruited after 1 January 2000, Results This analysis included 2500 people with RA (NOAR: 1000, ESPOIR: 766, ERAN: 734). ESPOIR included more women and the participants were younger [mean (standard deviation) age: NOAR: 57.1 (14.6), ESPOIR: 47.6 (12.5), ERAN: 56.8 (13.8); women: NOAR: 63.9%, ESPOIR: 76.9%, ERAN: 69.1%). Within each cohort, two pairs of trajectories following the hypothesized pattern (comparable DAS28-2Cs but different HAQs) were identified. Higher pain, fatigue and depressive symptoms were associated with increased odds of being in the high HAQ trajectories. Conclusion Excess disability is persistent in RA. Controlling inflammation may not be sufficient to alleviate disability in all people with RA, and effective pain, fatigue and mood management may be needed in some groups to improve long-term function.

Objectives: This study aimed to demonstrate how to estimate the value of health gain after patients with a multisystem disease achieve a condition-specific composite response endpoint. Methods: Data from patients treated in routine practice with an exemplar multisystem disease (systemic lupus erythematosus) were extracted from a national register (British Isles Lupus Assessment Group Biologics Register). Two bespoke composite response endpoints (Major Clinical Response and Improvement) were developed in advance of this study. Difference-in-differences regression compared health utility values (3-level version of EQ-5D; UK tariff) over 6 months for responders and nonresponders. Bootstrapped regression estimated the incremental quality-adjusted life-years (QALYs), probability of QALY gain after achieving the response criteria, and population monetary benefit of response. Results: Within the sample (n = 171), 18.2% achieved Major Clinical Response and 49.1% achieved Improvement at 6 months. Incremental health utility values were 0.0923 for Major Clinical Response and 0.0454 for Improvement. Expected incremental QALY gain at 6 months was 0.020 for Major Clinical Response and 0.012 for Improvement. Probability of QALY gain after achieving the response criteria was 77.6% for Major Clinical Response and 72.7% for Improvement. Population monetary benefit of response was £1 106 458 for Major Clinical Response and £649 134 for Improvement. Conclusions: Bespoke composite response endpoints are becoming more common to measure treatment response for multisystem diseases in trials and observational studies. Health technology assessment agencies face a growing challenge to establish whether these endpoints correspond with improved health gain. Health utility values can generate this evidence to enhance the usefulness of composite response endpoints for health technology assessment, decision making, and economic evaluation.

ObjectiveTo assess the feasibility of using smartwatches in people with knee osteoarthritis (OA) to determine the day-to-day variability of pain and the relationship between daily pain and step count.DesignObservational, feasibility study.SettingIn July 2017, the study was advertised in newspapers, magazines and, on social media. Participants had to be living/willing to travel to Manchester. Recruitment was in September 2017 and data collection was completed in January 2018.Participants26 participants aged>50 years with self-diagnosed symptomatic knee OA were recruited.Outcome measuresParticipants were provided with a consumer cellular smartwatch with a bespoke app that triggered a series of daily questions including two times per day questions about level of knee pain and one time per month question from the pain subscale of the Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire. The smartwatch also recorded daily step counts.ResultsOf the 25 participants, 13 were men and their mean age was 65 years (standard deviation (SD) 8 years). The smartwatch app was successful in simultaneously assessing and recording data on knee pain and step count in real time. Knee pain was categorised into sustained high/low or fluctuating levels, but there was considerable day-to-day variation within these categories. Levels of knee pain in general correlated with pain assessed by KOOS. Those with sustained high/low levels of pain had a similar daily step count average (mean 3754 (SD 2524)/4307 (SD 2992)), but those with fluctuating pain had much lower step count levels (mean 2064 (SD 1716)).ConclusionsSmartwatches can be used to assess pain and physical activity in knee OA. Larger studies may help inform a better understanding of causal links between physical activity patterns and pain. In time, this could inform development of personalised physical activity recommendations for people with knee OA.

Aims To determine if primary cemented acetabular component geometry (long posterior wall (LPW), hooded, or offset reorientating) influences the risk of revision total hip arthroplasty (THA) for instability or loosening. Methods The National Joint Registry (NJR) dataset was analyzed for primary THAs performed between 2003 and 2017. A cohort of 224,874 cemented acetabular components were included. The effect of acetabular component geometry on the risk of revision for instability or for loosening was investigated using log-binomial regression adjusting for age, sex, American Society of Anesthesiologists grade, indication, side, institution type, operating surgeon grade, surgical approach, polyethylene crosslinking, and prosthetic head size. A competing risk survival analysis was performed with the competing risks being revision for other indications or death. Results The distribution of acetabular component geometries was: LPW 81.2%; hooded 18.7%; and offset reorientating 0.1%. There were 3,313 (1.5%) revision THAs performed, of which 815 (0.4%) were for instability and 838 (0.4%) were for loosening. Compared to the LPW group, the adjusted subhazard ratio of revision for instability in the hooded group was 2.31 (p < 0.001) and 4.12 (p = 0.047) in the offset reorientating group. Likewise, the subhazard ratio of revision for loosening was 2.65 (p < 0.001) in the hooded group and 13.61 (p < 0.001) in the offset reorientating group. A time-varying subhazard ratio of revision for instability (hooded vs LPW) was found, being greatest within the first three months. Conclusion This registry-based study confirms a significantly higher risk of revision after cemented THA for instability and for loosening when a hooded or offset reorientating acetabular component is used, compared to a LPW component. Further research is required to clarify if certain patients benefit from the use of hooded or offset reorientating components, but we recommend caution when using such components in routine clinical practice. Cite this article: Bone Joint J 2021;103-B(11):1669–1677.

We assess how nitrogen oxides (NOx = NO + NO2), carbon monoxide (CO) and formaldehyde (HCHO) can be used as proxies to determine the combustion contribution to atmospheric carbon dioxide (CO2) using satellite observations. We focus our analysis on 2018 when there is a full complement of column data from the TROPOspheric Monitoring Instrument (NO2, CO, and HCHO) and the Orbiting Carbon Observatory-2 (CO2). We use the nested GEOS-Chem atmospheric chemistry model to relate high-resolution emission inventories over Europe to these atmospheric data, taking into account scene-dependent averaging kernels. We find that that NO2 and CO are the better candidates to identify incomplete combustion and fingerprints of different combustion sectors, but both have their own challenges associated with properly describing their atmospheric chemistry. The secondary source of HCHO from oxidation of biogenic volatile organic compounds, particularly over southern European countries, compromises its use as a proxy for combustion emissions. We find a weak positive correlation between the CO : CO2 inventory ratio and observed column enhancements of ΔCO : ΔCO2 (R

Surface observations have recorded large and incompletely understood changes to atmospheric methane (CH 4 ) this century. However, their ability to reveal the responsible surface sources and sinks is limited by their geographical distribution, which is biased towards the northern midlatitudes. Data from Earth-orbiting satellites designed specifically to measure atmospheric CH 4 have been available since 2009 with the launch of the Japanese Greenhouse gases Observing SATellite (GOSAT). We assess the added value of GOSAT to data collected by the US National Oceanic and Atmospheric Administration (NOAA), which have been the lynchpin for knowledge about atmospheric CH 4 since the 1980s. To achieve that we use the GEOS-Chem atmospheric chemistry transport model and an inverse method to infer a posteriori flux estimates from the NOAA and GOSAT data using common a priori emission inventories. We find the main benefit of GOSAT data is from its additional coverage over the tropics where we report large increases since the 2014/2016 El Niño, driven by biomass burning, biogenic emissions and energy production. We use data from the European TROPOspheric Monitoring Instrument to show how better spatial coverage and resolution measurements allow us to quantify previously unattainable diffuse sources of CH 4 , thereby opening up a new research frontier. This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 1)’.

Summary: Background: Factors that might influence response to systemic treatment for moderate‐to‐severe psoriasis are varied, and generally, are poorly understood, aside from high bodyweight, suggesting that other unidentified factors may be relevant in determining response to treatment. The impact of alcohol misuse on treatment response has not been previously investigated. Objectives: To investigate whether alcohol misuse is associated with poor response to treatment for psoriasis. Methods: This was a prospective cohort study in which response to systemic therapies was assessed using the Psoriasis Area and Severity Index (PASI). The CAGE (Cut down, Annoyed, Guilty, Eye opener) questionnaire was used to screen for alcohol misuse. A multivariable factional polynomial linear regression model was used to examine factors associated with change in PASI between baseline and follow‐up. Results: The cohort comprised 266 patients (biologic cohort, n = 134; conventional systemic cohort, n = 132). For the entire cohort, the median (interquartile range) PASI improved from 13 (10·0–18·3) at baseline to 3 (1·0–7·5) during follow‐up. A higher CAGE score [regression coefficient: 1·40, 95% confidence interval (CI) 0·04–2·77]; obesity (1·84, 95% CI 0·48–3·20); and receiving a conventional systemic rather than a biologic therapy (4·39, 95% CI 2·84–5·95) were significantly associated with poor response to treatment; whereas a higher baseline PASI (–0·83, 95% CI –0·92 to –0·74) was associated with a better response to treatment. Conclusions: The poor response to therapy associated with alcohol misuse and obesity found in people with psoriasis calls for lifestyle behaviour change interventions and support as part of routine clinical care. Targeting interventions to prevent, detect and manage alcohol misuse among people with psoriasis is needed to minimize adverse health consequences and improve treatment response.

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 (β=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.

OBJECTIVE: To determine the association between osteoarthritis (OA), rheumatoid arthritis (RA), and frailty and to determine whether comorbidities interact with OA and RA to further increase the likelihood of frailty.METHODS: Participants of the UK Biobank age 40-69 years at baseline were included. Demographic, lifestyle, and clinical data were collected at baseline and follow-up in a subset. Frailty was assessed using a frailty index (FI) (continuous) and a modified frailty phenotype (robust, pre-frail, frail). The association between RA and OA and frailty at baseline and follow-up was assessed using multiple regression models. We looked at whether comorbidities, including cardiovascular disease, diabetes mellitus, chronic obstructive pulmonary disease, and depression interacted additively with OA and RA to increase the likelihood of frailty.RESULTS: In total, 457,561 participants contributed data. Those with (versus without) RA (n = 4,894) and OA (n = 35,884), respectively, were more likely to be frail (adjusted relative risk ratio 10.7 [95% confidence interval (95% CI) 9.7, 11.7] and 3.4 [95% CI 3.3, 3.6]) and were more likely to have a higher FI at baseline. There was evidence of additive interaction between RA, OA, and common comorbidities increasing the occurrence of prevalent frailty. Among 25,163 participants included in longitudinal analysis, patients with RA (n = 202) and OA (n = 1,811) at baseline had an increased adjusted frailty incidence rate ratio (2.8 [95% CI 1.7, 4.6] and 1.7 [95% CI 1.3, 2.1], respectively) and also a higher FI during follow-up.CONCLUSION: Individuals with RA and OA are more likely to have, or develop, frailty. Common comorbidities interact with OA and RA to further increase the likelihood of frailty.

Atmospheric measurements can be used as a tool to evaluate national greenhouse gas inventories through inverse modelling. Using eight years of continuous methane (CH4) concentration data, this work assesses the United Kingdom's (UK) CH4 emissions over the period 2013–2020. Using two different inversion methods, we find mean emissions of 2.10 ± 0.09 Tg yr−1 and 2.12 ± 0.26 Tg yr−1 between 2013–2020, and an overall trend of −0.05 ± 0.01 Tg yr−2 and −0.06 ± 0.04 Tg yr−2, a 2–3 % decrease each year. This compares with the mean emissions of 2.23 Tg yr−1 and trend of −0.03 Tg yr−2 (1 % annual decrease) reported in the UK's 2021 inventory between 2013–2019. We examine how sensitive these estimates are to various components of the inversion set-up, such as the measurement network configuration, the prior emissions estimate, the inversion method, and the atmospheric transport model used. We find the decreasing trend to be due primarily to a reduction of emissions from England, which accounts for 70 % of the UK CH4 emissions. Comparisons during 2015 demonstrate consistency when different atmospheric transport models are used to map the relationship between sources and atmospheric observations at the aggregation level of the UK. The posterior annual national means and negative trend are found to be consistent across changes in network configuration. We show, using only two monitoring sites, the same conclusions on mean UK emissions and negative trend would be reached as using the full six-site network, albeit with larger posterior uncertainties. However, emissions estimates from Scotland fail to converge on the same posterior under different inversion setups, highlighting a shortcoming of the current observation network in monitoring all of the UK. Although CH4 emissions in 2020 are estimated to have declined relative to previous years, this decrease is in line with the longer-term emissions trend, and is not necessarily a response to national lockdowns.

Background Diabetic foot ulcers portend an almost twofold increase in all-cause mortality compared with diabetes on its own. Aim To investigate the association between diabetic foot ulcers and risk of death. Methods We performed a meta-analysis of all observational studies investigating the association between diabetic foot ulcers and all-cause mortality. Risk ratios and risk differences were pooled in a random-effects model. The I2 statistic was used to quantify heterogeneity between studies. Results Altogether, we identified 11 studies that reported 84 131 deaths from any cause in 446 916 participants with diabetes during a total of 643 499 person-years of follow-up. The crude event rate for all-cause mortality in individuals with diabetes who did not develop foot ulceration was 22% lower at 181.5 deaths (per 1000 person-years) than in those who developed foot ulcers (230.8 per 1000 person-years). Diabetic foot ulceration was associated with an increased risk of all-cause mortality (pooled relative risk 2.45, 95% CI 1.85-2.85). We did not observe any tangible differences in risk of all-cause mortality from diagnosis in studies reporting a mean duration of follow-up of ≤3 years (relative risk 2.43, 95% CI 2.27-2.61) or >3 years (relative risk 2.26, 95% CI 2.13-2.40) years. Funnel plot inspection revealed no significant publication bias among studies included in this meta-analysis. Conclusions Our study shows an excess rate of all-cause mortality in people with diabetic foot ulceration when compared to those without foot ulceration. It is imperative that early interventions to prevent foot ulceration and modify cardiovascular disease risk factors are put in place to reduce excess mortality.