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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.

It is well-known that mood and pain interact with each other, however individual-level variability in this relationship has been less well quantified than overall associations between low mood and pain. Here, we leverage the possibilities presented by mobile health data, in particular the “Cloudy with a Chance of Pain” study, which collected longitudinal data from the residents of the UK with chronic pain conditions. Participants used an App to record self-reported measures of factors including mood, pain and sleep quality. The richness of these data allows us to perform model-based clustering of the data as a mixture of Markov processes. Through this analysis we discover four endotypes with distinct patterns of co-evolution of mood and pain over time. The differences between endotypes are sufficiently large to play a role in clinical hypothesis generation for personalised treatments of comorbid pain and low mood.

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.

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.

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.

Background Psoriasis is a common, lifelong inflammatory skin disease, the severity of which can range from limited disease involving a small body surface area to extensive skin involvement. It is associated with high levels of physical and psychosocial disability and a range of comorbidities, including cardiovascular disease, and it is currently incurable. Objectives To (1) confirm which patients with psoriasis are at highest risk of developing additional long-term conditions and identify service use and costs to patient, (2) apply knowledge about risk of comorbid disease to the development of targeted screening services to reduce risk of further disease, (3) learn how patients with psoriasis cope with their condition and about their views of service provision, (4) identify the barriers to provision of best care for patients with psoriasis and (5) develop patient self-management resources and staff training packages to improve the lives of people with psoriasis. Design Mixed methods including two systematic reviews, one population cohort study, one primary care screening study, one discrete choice study, four qualitative studies and three mixed-methodology studies. Setting Primary care, secondary care and online surveys. Participants People with psoriasis and health-care professionals who manage patients with psoriasis. Results Prevalence rates for psoriasis vary by geographical location. Incidence in the UK was estimated to be between 1.30% and 2.60%. Knowledge about the cost-effectiveness of therapies is limited because high-quality clinical comparisons of interventions have not been done or involve short-term follow-up. After adjusting for known cardiovascular risk factors, psoriasis (including severe forms) was not found to be an independent risk factor for major cardiovascular events; however, co-occurrence of inflammatory arthritis was a risk factor. Traditional risk factors were high in patients with psoriasis. Large numbers of patients with suboptimal management of known risk factors were found by screening patients in primary care. Risk information was seldom discussed with patients as part of screening consultations, meaning that a traditional screening approach may not be effective in reducing comorbidities associated with psoriasis. Gaps in training of health-care practitioners to manage psoriasis effectively were identified, including knowledge about risk factors for comorbidities and methods of facilitating behavioural change. Theory-based, high-design-quality patient materials broadened patient understanding of psoriasis and self-management. A 1-day training course based on motivational interviewing principles was effective in increasing practitioner knowledge and changing consultation styles. The primary economic analysis indicated a high level of uncertainty. Sensitivity analysis indicated some situations when the interventions may be cost-effective. The interventions need to be assessed for long-term (cost-)effectiveness. Limitations The duration of patient follow-up in the study of cardiovascular disease was relatively short; as a result, future studies with longer follow-up are recommended. Conclusions Recognition of the nature of the psoriasis and its impact, knowledge of best practice and guideline use are all limited in those most likely to provide care for the majority of patients. Patients and practitioners are likely to benefit from the provision of appropriate support and/or training that broadens understanding of psoriasis as a complex condition and incorporates support for appropriate health behaviour change. Both interventions were feasible and acceptable to patients and practitioners. Cost-effectiveness remains to be explored. Future work Patient support materials have been created for patients and NHS providers. A 1-day training programme with training materials for dermatologists, specialist nurses and primary care practitioners has been designed. Spin-off research projects include a national study of responses to psoriasis therapy and a global study of the prevalence and incidence of psoriasis. A new clinical service is being developed locally based on the key findings of the Identification and Management of Psoriasis Associated ComorbidiTy (IMPACT) programme. Funding This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 10, No. 3. See the NIHR Journals Library website for further project information.

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.

Supplemental Digital Content is Available in the Text. Weather sensitivity among patients with chronic pain is a phenomenon more apparent in some participant subgroups., Introduction: Previous studies on the association between weather and pain severity among patients with chronic pain have produced mixed results. In part, this inconsistency may be due to differences in individual pain responses to the weather. Methods: To test the hypothesis that there might be subgroups of participants with different pain responses to different weather conditions, we examined data from a longitudinal smartphone-based study, Cloudy with a Chance of Pain, conducted between January 2016 and April 2017. The study recruited more than 13,000 participants and recorded daily pain severity on a 5-point scale (range: no pain to very severe pain) along with hourly local weather data for up to 15 months. We used a Bayesian multilevel model to examine the weather–pain association. Results: We found 1 in 10 patients with chronic pain were sensitive to the temperature, 1 in 25 to relative humidity, 1 in 50 to pressure, and 3 in 100 to wind speed, after adjusting for age, sex, belief in the weather–pain association, mood, and activity level. The direction of the weather–pain association differed between people. Although participants seem to be differentially sensitive to weather conditions, there is no definite indication that participants' underlying pain conditions play a role in weather sensitivity. Conclusion: This study demonstrated that weather sensitivity among patients with chronic pain is more apparent in some subgroups of participants. In addition, among those sensitive to the weather, the direction of the weather–pain association can differ.

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.

Background Systemic lupus erythematosus (SLE) is a heterogeneous systemic autoimmune condition for which there are limited licensed therapies. Clinical trial design is challenging in SLE due at least in part to imperfect outcome measures. Improved understanding of how disease activity changes over time could inform future trial design. The aim of this study was to determine whether distinct trajectories of disease activity over time occur in patients with active SLE within a clinical trial setting and to identify factors associated with these trajectories. Methods Latent class trajectory models were fitted to a clinical trial dataset of a monoclonal antibody targeting CD22 (Epratuzumab) in patients with active SLE using the numerical BILAG-2004 score (nBILAG). The baseline characteristics of patients in each class and changes in prednisolone over time were identified. Exploratory PK-PD modelling was used to examine cumulative drug exposure in relation to latent class membership. Results Five trajectories of disease activity were identified, with 3 principal classes: non-responders (NR), slow responders (SR) and rapid-responders (RR). In both the SR and RR groups, significant changes in disease activity were evident within the first 90 days of the trial. The SR and RR patients had significantly higher baseline disease activity, exposure to epratuzumab and activity in specific BILAG domains, whilst NR had lower steroid use at baseline and less change in steroid dose early in the trial. Conclusions Longitudinal nBILAG scores reveal different trajectories of disease activity and may offer advantages over fixed endpoints. Corticosteroid use however remains an important confounder in lupus trials and can influence early response. Changes in disease activity and steroid dose early in the trial were associated with the overall disease activity trajectory, supporting the feasibility of performing adaptive trial designs in SLE.

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.

We present Δ14CO2 observations and related greenhouse gas measurements at a background site in Ireland (Mace Head, MHD) and a tall tower site in the east of the UK (Tacolneston, TAC) that is more strongly influenced by fossil fuel sources. These observations have been used to calculate the contribution of fossil fuel sources to the atmospheric CO2 mole fractions; this can be done, as emissions from fossil fuels do not contain 14CO2 and cause a depletion in the observed Δ14CO2 value. The observations are compared to simulated values. Two corrections need to be applied to radiocarbon-derived fossil fuel CO2 (ffCO2): one for pure 14CO2 emissions from nuclear industry sites and one for a disequilibrium in the isotopic signature of older biospheric emissions (heterotrophic respiration) and CO2 in the atmosphere. Measurements at both sites were found to only be marginally affected by 14CO2 emissions from nuclear sites. Over the study period of 2014–2015, the biospheric correction and the correction for nuclear 14CO2 emissions were similar at 0.34 and 0.25 ppm ffCO2 equivalent, respectively. The observed ffCO2 at the TAC tall tower site was not significantly different from simulated values based on the EDGAR 2010 bottom-up inventory. We explored the use of high-frequency CO observations as a tracer of ffCO2 by deriving a constant ratio of CO enhancements to ffCO2 ratio for the mix of UK fossil fuel sources. This ratio was found to be 5.7 ppb ppm−1, close to the value predicted using inventories and the atmospheric model of 5.1 ppb ppm−1. The TAC site, in the east of the UK, was strategically chosen to be some distance from pollution sources so as to allow for the observation of well-integrated air masses. However, this distance from pollution sources and the large measurement uncertainty in 14CO2 lead to a large overall uncertainty in the ffCO2, being around 1.8 ppm compared to typical enhancements of 2 ppm.

Objectives To characterize the incidence of clinically diagnosed Paget’s disease of bone in the UK during 1999–2015 and to determine variations in the incidence of disease by age, sex, geography and level of deprivation. Methods Incident cases of Paget’s disease occurring between 1999 and 2015 were identified from primary care records. Overall crude incidence and incidence stratified by age and sex was calculated each year from 1999 to 2015. Direct age- and sex-standardized incidence was also calculated. We used Poisson regression to look at variations in incidence by deprivation and UK region. Results A total of 3592 incident cases of Paget’s disease were identified between 1999 and 2015. Incidence increased with age and at all ages was greater in men than women. In women and men, respectively, crude incidence increased from 0.037 and 0.074/10 000 population per year among those 45–49 years of age to 3.7 and 6.3/10 000 population per year among those ≥85 years. The overall standardized incidence decreased from 0.75/10 000 person-years in 1999 to 0.20/10 000 person-years in 2015. After adjustment for age and sex, incidence was >30% higher in the most- compared with least-deprived quintile of deprivation. There was evidence of geographic variation, with the highest incidence in the North West of England, which persisted after adjustment for age, sex and level of deprivation. Conclusion The incidence of clinically diagnosed Paget’s disease has continued to decrease since 1999. The reason for the decline in incidence remains unknown, although the rapidity of change points to an alteration in one or more environmental determinants.

Background/Aims In the real-world, tocilizumab is prescribed to a population of patients different from those prescribed TNF-inhibitors, often older with longer disease duration, worse functional status and more previous b- or tsDMARDs. The aim of this study was to evaluate if and how the risk of serious infection on tocilizumab and other bDMARDs differs when stratifying by line of therapy in a real-world population of rheumatoid arthritis patients. Methods We included patients registered in the BSRBR-RA treated with tocilizumab, etanercept, adalimumab, infliximab, certolizumab, abatacept or rituximab, including biosimilars. Primary outcome was the occurrence of a serious infection (defined as infection requiring hospitalisation, intravenous antibiotics or resulting in death). Primary covariate of interest was line of therapy (from first to fifth line of therapy). Every change to another b- or tsDMARD was considered a new line of therapy, but not a change between a bio-original and a biosimilar. Hazard ratios (HR) of serious infections were estimated using an inverse probability weighted Cox regression, based on a propensity score including baseline patient and disease characteristics, and adjusting for time in study (see table). The reference group was etanercept, which included the highest number of patients. Treatment exposure was analysed without and with stratification by line of therapy. Results A total of 33,916 treatment courses were included (Table) contributing to 62,532 years of follow-up. Compared to etanercept, participants starting abatacept, tocilizumab and rituximab were older, had more previous bDMARDs, longer disease duration and more comorbidities. The crude HR of serious infections were higher with infliximab and adalimumab, lower with certolizumab and rituximab, and not significantly different for abatacept and tocilizumab compared to etanercept. After adjustment, HR of serious infections were higher with tocilizumab, adalimumab and infliximab. However, when stratified by line of therapy, HR were no longer significantly different compared to etanercept for tocilizumab, adalimumab and infliximab for most lines of therapy. Conclusion Whilst initially there appears to be a difference in rates of serious infections between biologic therapies, line of therapy may be a confounding factor when comparing the risk of serious infections between bDMARDs. Disclosure K. Lauper: Honoraria; Gilead-Galapagos. Grants/research support; AbbVie. Other; AbbVie, Pfizer. L. Kearsley-Fleet: None. R. Davies: None. K. Watson: None. M. Lunt: None. K.L. Hyrich: Honoraria; AbbVie. Grants/research support; Pfizer, BMS.

Background/Aims People with osteoarthritis (OA) and rheumatoid arthritis (RA) are at increased risk of frailty, though the role of co-morbidities in contributing to frailty risk in these arthritides is uncertain. The aim of this study was i) to determine the association between common co-morbidities and frailty in OA and RA; and ii) to determine whether co-morbidities interact synergistically with OA and RA to increase the likelihood of frailty. Methods A cross-sectional analysis of the UK Biobank data was carried out. In this national cohort of participants aged 40-69 years, self-reported physician-diagnosed diseases including OA, RA, and common co-morbidities (including hypertension, coronary heart disease, diabetes, stroke/TIA, chronic obstructive pulmonary disease (COPD), and depression) were recorded. Frailty was assessed using a modification of the frailty phenotype (FP), comprising five components: self-reported weight loss, exhaustion, low physical activity (international activity questionnaire), slow walking speed, and low hand-grip strength. Pre-frailty and frailty, was identified based on the presence of 1-2 and ≥3 of these components, respectively. Among participants with OA and RA at baseline, the likelihood of being pre-frail or frail (vs not frail) at baseline among people with (vs without) each of the co-morbidities was assessed using multinomial logistic regression. To determine whether co-morbidities interact synergistically with OA and RA to increase the likelihood of frailty, deviation from additivity of risk was estimated by calculating the attributable proportion (AP) of risk due to biological interaction. An AP > 0 indicates positive (synergistic) biological interaction. Analyses were adjusted for age, sex, smoking status, BMI, and deprivation. Results In total, 457,561 people were included in the analysis; 35,884 (7.8%) had OA and 4,894 (1.1%) had RA. Overall, the mean (SD) age was 56.5 (8.1) years and 54% were female. The overall prevalence of frailty was 3.4%. The prevalence of frailty was higher among those with OA (10.0%) and RA (18.6%). Each of the co-morbidities considered was associated with increased relative risk of pre-frailty and frailty particularly COPD in OA, relative risk ratio (95%CI): pre-frailty, 2.09 (1.80, 2.42) and frailty, 4.45 (3.71, 5.33) and stroke/TIA in RA: pre-frailty, 1.97 (1.18, 3.29) and frailty, 3.64 (2.11, 6.29). Most of the co-morbidities considered interacted synergistically with OA and RA to increase the risk of pre-frailty and frailty, particularly diabetes in OA, AP (95% CI): pre-frailty, 0.13 (0.04, 0.23) and frailty, 0.49 (0.42, 0.55) and stroke/TIA in RA: pre-frailty, 0.34 (0.003, 0.68) and frailty 0.60 (0.38, 0.82). Conclusion Co-morbidity is associated with an increased occurrence of pre-frailty and frailty among people with OA and RA and interacts synergistically with OA and RA to increase the likelihood of pre-frailty and frailty. Disclosure M.J. Cook: None. M. Lunt: None. S.M.M. Verstappen: None. T.W. O'Neill: None.

There are concerns that immunomodulatory therapies may increase the risks of developing basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (SCC) in patients with moderate-severe psoriasis. A systematic review showed that psoriasis patients were significantly more likely to develop SCC than the general population, though included studies lacked adequate comparator cohorts and adjustment for relevant confounding factors including heterogeneity between BCC and SCC in association with phototherapy and immunomodulatory therapies and lacked data on newer biologic therapies. We therefore followed-up a large prospective patient cohort to determine whether the risks of developing BCC and SCC are increased in patients with psoriasis receiving biologic therapy compared with those treated with non-biologic systemic therapies only.

The natural ecosystems of tropical Africa represent a significant store of carbon, and play an important but uncertain role in the atmospheric budgets of carbon dioxide and methane. Recent studies using satellite data have concluded that methane emissions from this geographical region have increased since 2010 as a result of increased wetland extent, accounting for a third of global methane growth (Lunt et al 2019), and that the tropical Africa region dominates net carbon emission across the tropics (Palmer et al 2019). The conclusions of such studies are based on the accuracy of various satellite datasets and atmospheric transport models, over a geographical region where there are few independent observations available to check the robustness and validity of these datasets.Here we present the first ground-based observations of greenhouse gas (GHG) column concentrations over tropical East Africa, obtained using the University of Leicester EM27/SUN spectrometer during its deployment at the National Fisheries Resources Research Institute (NaFIRRI) in Jinja, Uganda. During the deployment we were able to operate the instrument remotely, using an automated weatherproof enclosure designed by the Technical University of Munich (Heinle and Chen 2018, Dietrich et al 2020). The instrument ran near-continuously for a three month period in early 2020, observing total atmospheric column concentrations of carbon dioxide and methane, along with other gases of interest including water vapour and carbon monoxide. We describe the data obtained during this period, processed using tools developed under the COCCON project (COllaborative Carbon Column Observing Network, Frey et al 2019), and demonstrate the value of performing GHG column measurements over tropical East Africa. We then evaluate the performance of CO2 observations from OCO-2 and CH4 from Sentinel 5P TROPOMI - datasets previously used in the studies of Palmer et al 2019 and Lunt et al 2019 respectively - and interpret the comparison with the ground-based observations in the light of data from the GEOS-Chem atmospheric chemistry transport model and the CAMS (Copernicus Atmospheric Monitoring Service) reanalyses.REFERENCES: Lunt, M. F., Palmer, P. I., Feng, L., Taylor, C. M., Boesch, H., and Parker, R. J.: An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data, Atmos. Chem. Phys., 19, 14721–14740, https://doi.org/10.5194/acp-19-14721-2019, 2019.Palmer, P.I., Feng, L., Baker, D., Chevallier, F., Boesch, H., and Somkuti, P.: Net carbon emissions from African biosphere dominate pan-tropical atmospheric CO2 signal. Nat Commun 10, 3344, https://doi.org/10.1038/s41467-019-11097-w, 2019.Heinle, L. and Chen, J.: Automated enclosure and protection system for compact solar-tracking spectrometers, Atmos. Meas. Tech., 11, 2173–2185, https://doi.org/10.5194/amt-11-2173-2018, 2018.Dietrich, F., Chen, J., Voggenreiter, B., Aigner, P., Nachtigall, N., and Reger, B.: Munich permanent urban greenhouse gas column observing network, Atmos. Meas. Tech. Discussions, 2020, 1–24, https://doi.org/10.5194/amt-2020-300, 2020.Frey, M. et al.: Building the COllaborative Carbon Column Observing Network (COCCON): long-term stabilityand ensemble performance of the EM27/SUN Fourier transform spectrometer, Atmos. Meas. Tech., 12, 1513–1530, https://doi.org/10.5194/amt-12-1513-2019, 2019

Airborne measurements of methane (CH4) were recorded over three major wetland areas in Zambia in February 2019 during the MOYA (Methane Observations and Yearly Assessments) ZWAMPS field campaign. Enhancements of up to 600 ppb CH4 were measured over the Bangweulu (11°36’ S, 30°05’ E), Kafue (15°43’ S, 27°17’ E), and Lukanga (14°29’ S, 27°47’ E) wetlands. Three independent methods were used to quantify methane emission fluxes; aircraft mass balance, aircraft eddy covariance, and atmospheric inversion modelling. Results yielded methane emission fluxes of 10-20 mg CH4 m-2 hr-1, which were up to an order of magnitude greater than the emission fluxes simulated by various wetland process models (WetCHARTs ensemble and LPX-Bern). Independent column CH4 observations from the TROPOMI instrument were used to verify these fluxes, and investigate their applicability for timescales longer than the duration of the MOYA flight campaign.

Results: In those without DM GC use had a 4.4-fold increased all-cause mortality RR (95% confidence interval (CI): 3.77 to 5.07) compared to non-use, whilst those with DM had a lower RR for GC use (2.99 (95% CI: 2.32, 3.87)). However, those with DM had a higher RD associated with GC use because of their higher baseline risk. In those with DM, GC use was associated with an additional 44.9 deaths/1000 person-years (pyrs) (95% CI: 32.9 to 56.8) compared to non-use, while in those without DM GC use was associated with an additional 34.4 deaths/1000 pyrs (95% CI: 30.1 to 38.7). A similar pattern was seen for CV mortality. The adjusted Cox proportional hazards model showed no evidence of multiplicative interaction, but additive interaction indicated a non-significant increased risk. For CV mortality there was no interaction on either scale.

To extend previous simulations on the performance of propensity score (PS) weighting and trimming methods to settings without and with unmeasured confounding, Poisson outcomes, and various strengths of treatment prediction (PS c statistic), we simulated studies with a binary intended treatment T as a function of 4 measured covariates. We mimicked treatment withheld and last-resort treatment by adding 2 “unmeasured” dichotomous factors that directed treatment to change for some patients in both tails of the PS distribution. The number of outcomes Y was simulated as a Poisson function of T and confounders. We estimated the PS as a function of measured covariates and trimmed the tails of the PS distribution using 3 strategies (“Crump,” “Stürmer,” and “Walker”). After trimming and reestimation, we used alternative PS weights to estimate the treatment effect (rate ratio): inverse probability of treatment weighting, standardized mortality ratio (SMR)-treated, SMR-untreated, the average treatment effect in the overlap population (ATO), matching, and entropy. With no unmeasured confounding, the ATO (123%) and “Crump” trimming (112%) improved relative efficiency compared with untrimmed inverse probability of treatment weighting. With unmeasured confounding, untrimmed estimates were biased irrespective of weighting method, and only Stürmer and Walker trimming consistently reduced bias. In settings where unmeasured confounding (e.g., frailty) may lead physicians to withhold treatment, Stürmer and Walker trimming should be considered before primary analysis.

Importance Treatments for psoriasis may be less effective in everyday practice than in clinical trials. Emulating a target trial using data from the British Association of Dermatologists Biologics and Immunomodulators Register (BADBIR) can provide treatment effect estimates that are robust and can inform both clinicians and regulatory bodies. Objectives To assess the comparative effectiveness of ustekinumab and secukinumab in patients with psoriasis, and to test whether the relative effectiveness estimate of the CLEAR trial, a randomized clinical trial that compared secukinumab with ustekinumab for psoriasis, can be replicated. Design, Setting, and Participants This comparative effectiveness research study used a target trial emulation approach and was performed between November 2007 and August 2019. Data were obtained from BADBIR, a multicenter longitudinal pharmacovigilance register of patients with moderate to severe psoriasis in the United Kingdom and Republic of Ireland. Participants had chronic plaque psoriasis, were 18 years or older, and had at least 1 record of a Psoriasis Area and Severity Index (PASI) of 12 or higher before their initiation to secukinumab or ustekinumab. Propensity score (PS) 1:1 matched analysis and inverse probability treatment weighted analysis were performed. Main Outcomes and Measures The primary outcomes were the risk ratio (RR) and the risk difference (RD) for achieving PASI of 2 or lower after 12 months of therapy for secukinumab compared with ustekinumab. Methods to account for missing outcome data were complete case analysis, nonresponder imputation, last observation carried forward, inverse probability of censoring weighting, and multiple imputation. Regulatory and estimate agreement metrics were used to benchmark the effect estimates in this study against those in the CLEAR trial. Results A total of 1231 patients were included in the analysis, with 917 receiving ustekinumab and 314 receiving secukinumab. Secukinumab was superior to ustekinumab in all analyses, except under the nonresponder imputation method, in the proportion of participants achieving a PASI of 2 or lower (PS-weighted complete case analysis: RR, 1.28 [95% CI, 1.06-1.55]; RD, 11.9% [1.6-22.1]). All analyses, except for nonresponder imputation, reached regulatory agreement in both PS-matching and PS-weighted analyses. Conclusions and Relevance This comparative effectiveness study found that secukinumab resulted in more patients achieving a PASI of 2 or lower after 12 months of therapy compared with ustekinumab in patients with psoriasis. Target trial emulation in this study resulted in regulatory and estimate agreement with the CLEAR randomized clinical trial; further such studies may help fill the evidence gap when comparing other systemic therapies for psoriasis.

With sustained growth of diabetes numbers, sustained patient engagement is essential. Using nationally available data, we have shown that the higher mortality associated with a diagnosis of T1DM/T2DM could produces loss of 6.4 million future life years in the current UK population. In the model, the 'average' person with T1DM (age 42.8 years) has a life expectancy from now of 32.6 years, compared to 40.2 years in the equivalent age non diabetes mellitus population, corresponding to lost life years (LLYs) of 7.6 years/average person. The 'average' person with T2DM (age 65.4 years) has a life expectancy from now of 18.6 years compared to the 20.3 years for the equivalent non diabetes mellitus population, corresponding to LLY of 1.7 years/average person. We estimate that for both T1DM and T2DM, one year with HbA1c >58 mmol/mol loses around 100 life days. Linking glycaemic control to mortality has the potential to focus minds on effective engagement with therapy and lifestyle recommendation adherence.

Background Propensity scores are widely used to deal with confounding bias in medical research. An incorrectly specified propensity score model may lead to residual confounding bias; therefore it is essential to use diagnostics to assess propensity scores in a propensity score analysis. The current use of propensity score diagnostics in the medical literature is unknown. The objectives of this study are to (1) assess the use of propensity score diagnostics in medical studies published in high-ranking journals, and (2) assess whether the use of propensity score diagnostics differs between studies (a) in different research areas and (b) using different propensity score methods. Methods A PubMed search identified studies published in high-impact journals between Jan 1st 2014 and Dec 31st 2016 using propensity scores to answer an applied medical question. From each study we extracted information regarding how propensity scores were assessed and which propensity score method was used. Research area was defined using the journal categories from the Journal Citations Report. Results A total of 894 papers were included in the review. Of these, 187 (20.9%) failed to report whether the propensity score had been assessed. Commonly reported diagnostics were p-values from hypothesis tests (36.6%) and the standardised mean difference (34.6%). Statistical tests provided marginally stronger evidence for a difference in diagnostic use between studies in different research areas (p = 0.033) than studies using different propensity score methods (p = 0.061). Conclusions The use of diagnostics in the propensity score medical literature is far from optimal, with different diagnostics preferred in different areas of medicine. The propensity score literature may improve with focused efforts to change practice in areas where suboptimal practice is most common.

Background The US opioid epidemic has led to similar concerns about prescribed opioids in the UK. In new users, initiation of or escalation to more potent and high dose opioids may contribute to long-term use. Additionally, physician prescribing behaviour has been described as a key driver of rising opioid prescriptions and long-term opioid use. No studies to our knowledge have investigated the extent to which regions, practices, and prescribers vary in opioid prescribing whilst accounting for case mix. This study sought to (i) describe prescribing trends between 2006 and 2017, (ii) evaluate the transition of opioid dose and potency in the first 2 years from initial prescription, (iii) quantify and identify risk factors for long-term opioid use, and (iv) quantify the variation of long-term use attributed to region, practice, and prescriber, accounting for case mix and chance variation. Methods and findings A retrospective cohort study using UK primary care electronic health records from the Clinical Practice Research Datalink was performed. Adult patients without cancer with a new prescription of an opioid were included; 1,968,742 new users of opioids were identified. Mean age was 51 ± 19 years, and 57% were female. Codeine was the most commonly prescribed opioid, with use increasing 5-fold from 2006 to 2017, reaching 2,456 prescriptions/10,000 people/year. Morphine, buprenorphine, and oxycodone prescribing rates continued to rise steadily throughout the study period. Of those who started on high dose (120–199 morphine milligram equivalents [MME]/day) or very high dose opioids (≥200 MME/day), 10.3% and 18.7% remained in the same MME/day category or higher at 2 years, respectively. Following opioid initiation, 14.6% became long-term opioid users in the first year. In the fully adjusted model, the following were associated with the highest adjusted odds ratios (aORs) for long-term use: older age (≥75 years, aOR 4.59, 95% CI 4.48–4.70, p < 0.001; 65–74 years, aOR 3.77, 95% CI 3.68–3.85, p < 0.001, compared to, In this analysis of electronic health records, Meghna Jani and colleagues investigate how opioids are prescribed in UK primary care patients., Author summary Why was this study done? Whilst opioid prescribing for non-cancer pain has risen in the US and Canada, trends over time are less clear in the UK. No studies to our knowledge have evaluated how opioid dose/potency changes over time in UK patients started an opioid for the first time for non-cancer pain, to assess escalation, tapering, and long-term use. Physician prescribing behaviour has been implicated as a key driver of rising opioid prescriptions and long-term opioid use; however, this needs to be interpreted in the context of regional and individual patient differences. The association of region, practice, prescriber, and individual factors with long-term opioid use is highly important, as this has implications for policy and future targeted public health interventions. What did the researchers do and find? We conducted a study of 1,968,742 new opioid users without cancer from primary care electronic health records across the UK. We found that between 2006 and 2017 codeine was the most commonly prescribed opioid: There was a 5-fold increase in codeine prescriptions, a 7-fold increase in tramadol prescriptions, and a 30-fold increase in oxycodone prescriptions for non-cancer pain. Prescribing factors (e.g., high dose/potency of opioid or concurrent gabapentinoid use), older age, higher socioeconomic deprivation score, and other conditions including fibromyalgia, rheumatological conditions, history of substance abuse, suicide/self-harm, alcohol abuse, and major surgery were associated with long-term opioid use. After accounting for individual patient factors, the North West, Yorkshire and the Humber, and South West regions of England were associated with a higher risk of long-term opioid use. Whilst there were only 3.5% of prescribers who had significantly higher prescribing practices leading to long-term use after adjustment of patient factors, where they did, rates were up to 3.5 times higher than the population average. What do these findings mean? Clinicians should take care in prescribing high dose opioids at initiation and closely monitor those with the above individual factors for long-term use. The variation observed across regions, practices, and prescribers after adjustment for patient factors supports calls for action to reduce such variation and harmonise prescribing practices.

IntroductionEcological studies show association between antimicrobial resistance (AMR), and inappropriate oral antibiotics use. Moderating antibiotic prescribing requires an understanding of all drivers of local prescribing. The aim was to quantify how much is determined by external factors compared with discretionary clinical choices.MethodsOral antibiotic usage taken from England General Practitioner/Family Doctor practice prescribing data was aggregated using WHO/ATC defined daily doses (DDDs). The average annual antibiotic daily prescribing rate (AAADPR) in each practice was the total DDD of oral antibiotics divided by registered population and 365. The AAADPR of English practices in 2017_18 was linked by regression to factors including demographics, geography, medical comorbidities, clinical performance, patient satisfaction, medical workforce characteristics and prescribing selection. The regression coefficients for modifiable prescribing selection factors were applied to the difference between the median and top decile practice values to establish overall reduction opportunities through changing prescribing behaviour.ResultsTwenty five factors accounted for 58% of the AAADPR variation in 5889 practices supporting 49.8 million patients. Non‐modifiable factors linked increased AAADPR to more northerly location, higher prevalence of diabetes, COPD, CHD, and asthma; higher white ethnicity; higher patient satisfaction and lower population density. Modifiable behaviour accounted for 11% of the variation in AAADPR, with increases associated with a wider range of antibiotics, higher proportion taken as liquids, higher doses in each prescription, lower guideline compliance, lower targeted antibiotics, lower spend/dose, and less seasonal variation. If all practices achieved the level of modifiable factors of the top decile, this model suggests that overall AAADPR could reduce by 31%.ConclusionSuch analysis is associative and does not infer causation. However, demographics, location, medical condition of the population, and prescribing selection are drivers of overall antibiotic prescribing. This analysis provides benchmarks for both non‐modifiable and modifiable factors against which practices could evaluate their opportunities to reduce antibiotic prescribing.