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Physical inactivity is common during periods of self-isolation, but for patients with rheumatic diseases, there are crucial benefits to be gained from maintaining an active lifestyle throughout the COVID-19 pandemic. Patients should be provided with support to maintain physical activity and avoid prolonged periods of time spent sitting.

Juvenile idiopathic arthritis (JIA) is an umbrella term for arthritis of unknown origin, lasting for >6 weeks with onset before 16 years of age. JIA is the most common chronic inflammatory rheumatic condition of childhood. According to the International League Against Rheumatism (ILAR) classification, seven mutually exclusive categories of JIA exist based on disease manifestations during the first 6 months of disease. Although the ILAR classification has been useful to foster research, it has been criticized mainly as it does not distinguish those forms of chronic arthritis observed in adults and in children from those that may be unique to childhood. Hence, efforts to provide a new evidence-based classification are ongoing. Similar to arthritis observed in adults, pathogenesis involves autoimmune and autoinflammatory mechanisms. The field has witnessed a remarkable improvement in therapeutic possibilities of JIA owing to the availability of new potent drugs and the possibility to perform controlled trials with support from legislative interventions and large networks availability. The goal of drug therapy in JIA is to rapidly reduce disease activity to inactive disease or clinical remission, minimize drug side effects and achieve a quality of life comparable to that of healthy peers. As JIA can influence all aspects of a child’s and their family’s life, researchers increasingly recognize improvement of health-related quality of life as a key treatment goal. This Primer by Martini and colleagues summarizes the epidemiology, pathophysiology, diagnosis and management of Juvenile idiopathic arthritis (JIA), the most common chronic inflammatory rheumatic condition of childhood. In addition, this Primer discusses the quality of life of children with JIA and reviews future research directions to improve patient care.

During the COVID-19 pandemic, the need to provide high-level care for a large number of patients with COVID-19 has affected resourcing for, and limited the routine care of, all other conditions. The impact of this health emergency is particularly relevant in the rare connective tissue diseases (rCTDs) communities, as discussed in this Perspective article by the multi-stakeholder European Reference Network on Rare and Complex Connective Tissue and Musculoskeletal Diseases (ERN ReCONNET). The clinical, organizational and health economic challenges faced by health-care providers, institutions, patients and their families during the SARS-CoV-2 outbreak have demonstrated the importance of ensuring continuity of care in the management of rCTDs, including adequate diagnostics and monitoring protocols, and highlighted the need for a structured emergency strategy. The vulnerability of patients with rCTDs needs to be taken into account when planning future health policies, in preparation for not only the post-COVID era, but also any possible new health emergencies.In this Perspective article, members of the European Reference Network on Rare and Complex Connective Tissue and Musculoskeletal Diseases discuss clinical and organizational challenges in this community caused by the COVID-19 pandemic and what lessons might be learned for the future.

Biologic and targeted synthetic disease-modifying antirheumatic drugs (ts/bDMARDs) play a pivotal role in the treatment of rheumatoid arthritis (RA), psoriatic arthritis (PsA), and ankylosing spondylitis (AS). Persistence of therapy provides an index of a drug’s overall effectiveness. The objective of the study was to identify factors associated with discontinuation of ts/bDMARDs in a real-world dataset. The study population comprised patients diagnosed with RA, PsA, and AS included in the BIOBADASER registry for whom follow-up data were available until November 2019. Patient features and treatment data were included in the analysis. The Kaplan–Meier method was used to study survival of the different drugs according to the reason for discontinuation. Factors associated with discontinuation were studied using Cox regression models and bivariate and multivariate analyses. P values of less than 0.05 were regarded as statistically significant. The study population comprised 4,752 patients who received a total of 8,377 drugs, of which 4,411 (52.65%) were discontinued. The Kaplan–Meier curves showed that survival for first-line treatment was greater in all 3 groups (p < 0.001). Patients with RA had a greater risk of discontinuation if they were younger (HR, 0.99; 95% CI 0.99–1.00), if they were receiving anti-TNFα agents (HR, 0.61; 95% CI 0.54–0.70), and if they had more comorbid conditions (HR, 1.09; 95% CI 1.00–1.17). Patients with PsA had a higher risk if they were women (HR, 1.36; 95% CI 1.15–1.62) and if they were receiving other ts/bDMARDs (HR, 1.29; 95% CI 1.05–1.59). In patients with AS, risk increased with age (HR, 1.01; 95% CI 1.00–1.02), as did the number of comorbid conditions (HR, 1.27; 95% CI 1.12–1.45). The factors that most affected discontinuation of ts/bDMARDs were line of treatment, age, type of drug, sex, comorbidity and the year of initiation of treatment. The association with these factors differed with each disease, except for first-line treatment, which was associated with a lower risk of discontinuation in all 3 diseases.

Machine learning (ML) is a computerized analytical technique that is being increasingly employed in biomedicine. ML often provides an advantage over explicitly programmed strategies in the analysis of multidimensional information by recognizing relationships in the data that were not previously appreciated. As such, the use of ML in rheumatology is increasing, and numerous studies have employed ML to classify patients with rheumatic autoimmune inflammatory diseases (RAIDs) from medical records and imaging, biometric or gene expression data. However, these studies are limited by sample size, the accuracy of sample labelling, and absence of datasets for external validation. In addition, there is potential for ML models to overfit or underfit the data and, thereby, these models might produce results that cannot be replicated in an unrelated dataset. In this Review, we introduce the basic principles of ML and discuss its current strengths and weaknesses in the classification of patients with RAIDs. Moreover, we highlight the successful analysis of the same type of input data (for example, medical records) with different algorithms, illustrating the potential plasticity of this analytical approach. Altogether, a better understanding of ML and the future application of advanced analytical techniques based on this approach, coupled with the increasing availability of biomedical data, may facilitate the development of meaningful precision medicine for patients with RAIDs.In this Review, the authors provide an introduction to machine learning and discuss the use of this approach in rheumatic autoimmune inflammatory diseases, including the classification of patients based on medical records or molecular characteristics, identification of novel biomarkers or drug repurposing candidates and prediction of disease progression or onset.

Algorithms based on Empirical Mode Decomposition (EMD) and Iterative Filtering (IF) are largely implemented for representing a signal as superposition of simpler well-behaved components called Intrinsic Mode Functions (IMFs). Although they are more suitable than traditional methods for the analysis of nonlinear and nonstationary signals, they could be easily misused if their known limitations, together with the assumptions they rely on, are not carefully considered. In this work, we examine the main pitfalls and provide caveats for the proper use of the EMD- and IF-based algorithms. Specifically, we address the problems related to boundary errors, to the presence of spikes or jumps in the signal and to the decomposition of highly-stochastic signals. The consequences of an improper usage of these techniques are discussed and clarified also by analysing real data and performing numerical simulations. Finally, we provide the reader with the best practices to maximize the quality and meaningfulness of the decomposition produced by these techniques. In particular, a technique for the extension of signal to reduce the boundary effects is proposed; a careful handling of spikes and jumps in the signal is suggested; the concept of multi-scale statistical analysis is presented to treat highly stochastic signals.

Key Points Ectopic lymphoid structures (ELSs) develop in the target organs of a subset of patients with rheumatic autoimmune diseases and recapitulate key cellular and molecular features normally present in secondary lymphoid organs ELSs in rheumatic autoimmune diseases can function as germinal centres, favouring B cell selection and plasma cell differentiation B cells and plasma cells associated with ELSs in rheumatic autoimmune diseases frequently display an autoreactive phenotype towards disease-specific autoantigens Ectopic germinal centres in patients with Sjögren syndrome have been associated with more severe systemic manifestations and a higher risk of B cell lymphoma In rheumatoid arthritis, emerging but as-yet-inconclusive evidence suggests a role for ELSs in influencing disease evolution and the response to conventional and biologic treatments Several candidate therapeutic agents that target ELS-associated pathways are currently in clinical trials for rheumatic autoimmune diseases Ectopic lymphoid structures have been identified in the target organs of a subset of patients with rheumatic autoimmune diseases. This Review describes these structures and summarizes our current understanding of how they form, function and contribute to autoimmunity. Ectopic lymphoid neogenesis often occurs in the target tissues of patients with chronic rheumatic autoimmune diseases such as rheumatoid arthritis, Sjögren syndrome and other connective tissue disorders, including systemic lupus erythematosus and myositis. However, the mechanisms of ectopic lymphoid-like structure (ELS) formation and function are not entirely understood. For example, it is unclear whether ELSs indicate distinct disease phenotypes or whether they are evolutionary manifestations of chronic inflammation. Also unclear is why ELSs form in some patients but not in others. Nonetheless, ELSs frequently display functional features of ectopic germinal centres and can actively contribute to the maintenance of autoimmunity through the production of disease-specific autoantibodies; furthermore, they seem to influence disease severity and response to both synthetic and biologic DMARDs. In this Review, we discuss current knowledge and gaps in understanding of ELS formation and function including their prevalence in the above rheumatic autoimmune diseases; the mechanisms underlying their formation, maintenance and function, including positive and negative regulatory pathways; their functional relevance in the perpetuation of autoimmunity; their relationship with disease phenotypes, clinical outcomes and response to treatment; and the potential for specific targeting of ELSs through novel therapeutic modalities.

Key Points Patients with inflammatory joint diseases (IJDs) have an increased burden of cardiovascular disease compared with the general population Inflammation and traditional risk factors contribute to the cardiovascular risk associated with IJDs IJDs and atherosclerosis are thought to have a common, inflammatory pathogenesis Cardiovascular risk management is unsatisfactory in patients with IJD The main pillars of cardiovascular management in IJD are pharmacological and nonpharmacological approaches to reduce cardiovascular risk factors, along with tight control of disease activity Coordination of care between rheumatologists, internists, cardiologists and primary-care physicians should be increased to optimize management of cardiovascular risk in patients with IJD The burden of cardiovascular disease is high in patients with inflammatory joint disease, owing to the presence of inflammation and traditional cardiovascular risk factors. Current management of cardiovascular risk factors and control of disease activity are unsatisfactory, and patients could benefit from improvements in screening and coordination between the cardiology and rheumatology branches of health care. Patients with rheumatoid arthritis (RA) and other inflammatory joint diseases (IJDs) have an increased risk of premature death compared with the general population, mainly because of the risk of cardiovascular disease, which is similar in patients with RA and in those with diabetes mellitus. Pathogenic mechanisms and clinical expression of cardiovascular comorbidities vary greatly between different rheumatic diseases, but atherosclerosis seems to be associated with all IJDs. Traditional risk factors such as age, gender, dyslipidaemia, hypertension, smoking, obesity and diabetes mellitus, together with inflammation, are the main contributors to the increased cardiovascular risk in patients with IJDs. Although cardiovascular risk assessment should be part of routine care in such patients, no disease-specific models are currently available for this purpose. The main pillars of cardiovascular risk reduction are pharmacological and nonpharmacological management of cardiovascular risk factors, as well as tight control of disease activity.

TNF-alpha inhibitors have revolutionized the therapeutic care in chronic inflammatory diseases. Several biosimilar products were commercialized at their patent expiry, substantially decreasing the cost of treatment. This longitudinal descriptive study aimed at assessing infliximab, etanercept and adalimumab biosimilar penetration rates using data of the French National Health Data System. A total of 207,118 new or prevalent users from the date of first biosimilar commercialization in France (respectively January 2015, May 2016 and October 2018) were included in the study and followed until September 30, 2021. Biosimilars represented respectively 78%, 46% and 53% of the overall initiations, and 94%, 66% and 60% last year’s initiations. A total of 46%, 19% and 17% of originator product prevalent users switched for a biosimilar during the follow-up. Biosimilar penetration rate was much higher for infliximab than for its counterparts, due to its hospital delivery modality. Biosimilar initiation and originator-to-biosimilar switch tended to be observed more in rheumatology than in the other specialties. Biosimilar use was mostly consistent across patient socio-demographic characteristics. Biosimilar initiation rate increased rapidly from their market arrival and originator-to-biosimilar switch rate remained moderate, highlighting the need and usefulness of political action and biosimilar use tracking.

This study investigates the prevalence of dyslipidemia and its association with disease activity in children with Juvenile Dermatomyositis (JDM). A retrospective chart review of 142 JDM patients who had fasting lipid profiles was conducted. Clinical, and laboratory indicators of disease activity at the time of lipid assessment were obtained. JDM patients displayed a high prevalence (72%) of abnormal or borderline fasting lipid profiles, particularly involving HDL and triglycerides. Treatment-naïve patients exhibited the most significant dyslipidemia, with significantly lower median HDL levels compared to those on medication (30 vs. 49 mg/dL, p  < 0.0001). HDL levels inversely correlated with various disease activity measures, including disease activity score (DAS) total ( r = -0.38, p  < 0.001), DAS muscle weakness ( r = -0.5, p  < 0.001), DAS skin ( r = -0.25, p  = 0.003), neopterin ( r = -0.41, p  < 0.001), ESR ( r = -0.25, p  = 0.006), and vWF Ag ( r = -0.21, p  = 0.02). In conclusion, JDM patients have a high prevalence of dyslipidemia, especially low HDL and elevated triglycerides. The severity of dyslipidemia (low HDL) correlates with disease activity, with treatment-naïve patients demonstrating the lowest HDL levels. These findings suggest the importance of annual lipid profile monitoring in JDM patients, potentially followed by early interventions such as dietary adjustments and exercise programs.