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Lack of standardization of outcome measures limits the usefulness of clinical trial evidence to inform health care decisions. This can be addressed by agreeing on a minimum core set of outcome measures per health condition, containing measures relevant to patients and decision makers. Since 1992, the Outcome Measures in Rheumatology (OMERACT) consensus initiative has successfully developed core sets for many rheumatologic conditions, actively involving patients since 2002. Its expanding scope required an explicit formulation of its underlying conceptual framework and process. Literature searches and iterative consensus process (surveys and group meetings) of stakeholders including patients, health professionals, and methodologists within and outside rheumatology. To comprehensively sample patient-centered and intervention-specific outcomes, a framework emerged that comprises three core “Areas,” namely Death, Life Impact, and Pathophysiological Manifestations; and one strongly recommended Resource Use. Through literature review and consensus process, core set development for any specific health condition starts by identifying at least one core “Domain” within each of the Areas to formulate the “Core Domain Set.” Next, at least one applicable measurement instrument for each core Domain is identified to formulate a “Core Outcome Measurement Set.” Each instrument must prove to be truthful (valid), discriminative, and feasible. In 2012, 96% of the voting participants (n=125) at the OMERACT 11 consensus conference endorsed this model and process. The OMERACT Filter 2.0 explicitly describes a comprehensive conceptual framework and a recommended process to develop core outcome measurement sets for rheumatology likely to be useful as a template in other areas of health care.

The cellular complexity and functional diversity of the human immune system necessitate the use of high-dimensional single-cell tools to uncover its role in multifaceted diseases such as rheumatic diseases, as well as other autoimmune and inflammatory disorders. Proteomic technologies that use elemental (heavy metal) reporter ions, such as mass cytometry (also known as CyTOF) and analogous high-dimensional imaging approaches (including multiplexed ion beam imaging (MIBI) and imaging mass cytometry (IMC)), have been developed from their low-dimensional counterparts, flow cytometry and immunohistochemistry, to meet this need. A growing number of studies have been published that use these technologies to identify functional biomarkers and therapeutic targets in rheumatic diseases, but the full potential of their application to rheumatic disease research has yet to be fulfilled. This Review introduces the underlying technologies for high-dimensional immune monitoring and discusses aspects necessary for their successful implementation, including study design principles, analytical tools and future developments for the field of rheumatology.Single-cell proteomic techniques that use elemental (heavy metal) reporter ions increase the number of parameters that can be studied at once in whole tissues. This Review discusses the practical aspects of using such technologies in rheumatic disease research.

ObjectivesClassification criteria are biased towards classifying long-standing disease. We compared the European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR)-2019, Systemic Lupus International Collaborating Clinics (SLICC)-2012 and ACR-1997 criteria in an early (median 48 months) systemic lupus erythematosus (SLE) cohort.MethodsPatients diagnosed with SLE (n=690) or control diseases (n=401). Sensitivity, specificity of the criteria and time-to-classification were calculated. Modified classification algorithms were derived from a random 80% and validated in the remaining 20% of the dataset running multiple iterations.ResultsAt last assessment, sensitivities of ACR-1997, SLICC-2012 and EULAR/ACR-2019 criteria were 85.7%, 91.3% and 88.6%, with specificities 93.0%, 93.8% and 97.3%, respectively. Both SLICC and EULAR/ACR enabled earlier classification. Only 76.7% of patients with SLE met all three criteria suggesting non-overlapping groups. Notably, unclassified patients had high prevalence of British Isles Lupus Assessment Group moderate/severe manifestations (43.3%–60%) and SLICC/ACR organ damage (30%–50%). At diagnosis, criteria missed 25.6%–30.5% of patients. Modification of EULAR/ACR and SLICC algorithms to include hypocomplementaemia and/or positive anti-phospholipid antibodies as alternative entry criterion, and/or allow classification with fewer clinical criteria from multiple organs, increased their sensitivity at diagnosis (median 82.0% and 86.2%) and overall (93.7% and 97.1%) with modest decreases in specificity. Importantly, patients who were still missed by the modified criteria had lower incidence of major organ involvement, use of immunosuppressive/biological therapies and organ damage.ConclusionsThe SLICC and EULAR/ACR are more sensitive than the ACR and the EULAR/ACR criteria have superior specificity in early SLE, although patients with significant disease can be missed. Combination and/or modification of the classification algorithms may enhance their sensitivity, allowing earlier classification and treatment of more patients with high disease burden.

Rheumatology faces a critical shortage of health-care professionals, exacerbated by an ageing patient population and escalating costs, resulting in widening gaps in care. Exponential advances in digital health technologies (DHTs) in the past 5 years offer new opportunities to address these challenges and could contribute to overall improved health care. However, keeping pace with innovations and integrating them into clinical practice can be challenging. This Review explores the transformative potential of DHTs for rheumatology in reshaping the entire patient pathway and redefining the roles of patients and providers, and discusses the potential barriers to DHT integration. Key technologies, such as large language models, clinical decision-support systems, digital therapeutics, electronic patient-reported outcomes, digital biomarkers, robots, self-sampling devices and artificial intelligence-based scribes, can be implemented along the patient pathway. A digital-first hybrid stepped-care patient pathway could combine in-person and remote care, enabling personalized and continuous monitoring through a digital safety net. The potential benefits and risks of transforming the traditional patient–provider relationship into a digital health triad with technology are discussed. Collaborative efforts are needed to navigate the evolving digital health landscape and harness the potential of DHTs to improve rheumatology care.Digital health has the potential to improve patient care in rheumatology and alleviate strain on the health-care system. This Review explores the current status of the transition from traditional health care to a model that harnesses the potential of digital health technologies, including discussion of the main benefits and barriers.

Background/objectivesThe European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) 2019 classification criteria for systemic lupus erythematosus system showed high specificity, while attaining also high sensitivity. We hereby analysed the performance of the individual criteria items and their contribution to the overall performance of the criteria.MethodsWe combined the EULAR/ACR derivation and validation cohorts for a total of 1197 systemic lupus erythematosus (SLE) and n=1074 non-SLE patients with a variety of conditions mimicking SLE, such as other autoimmune diseases, and calculated the sensitivity and specificity for antinuclear antibodies (ANA) and the 23 specific criteria items. We also tested performance omitting the EULAR/ACR criteria attribution rule, which defines that items are only counted if not more likely explained by a cause other than SLE.ResultsPositive ANA, the new entry criterion, was 99.5% sensitive, but only 19.4% specific, against a non-SLE population that included other inflammatory rheumatic, infectious, malignant and metabolic diseases. The specific criteria items were highly variable in sensitivity (from 0.42% for delirium and 1.84% for psychosis to 75.6% for antibodies to double-stranded DNA), but their specificity was uniformly high, with low C3 or C4 (83.0%) and leucopenia <4.000/mm³ (83.8%) at the lowest end. Unexplained fever was 95.3% specific in this cohort. Applying the attribution rule improved specificity, particularly for joint involvement.ConclusionsChanging the position of the highly sensitive, non-specific ANA to an entry criterion and the attribution rule resulted in a specificity of >80% for all items, explaining the higher overall specificity of the criteria set.

Online social networking offers numerous opportunities for continuing medical education, professional development, and scholarly collaboration. Available social media channels proved useful for expanding education and research perspectives, particularly in rapidly developing academic disciplines such as rheumatology. Although there are numerous advantages of social media, busy clinicians should be aware of some drawbacks related to misinformation, unethical promotion, and unprofessional behavior in globally expanding platforms. Filtering credible and expert-proven information by skilled users is, therefore, increasingly important. Enforcing ethical norms and advancing professional etiquette in the field is strongly advisable. This article overviews the advantages and shortcomings of social media and reflects on available platforms for education and research in rheumatology.

European League Against Rheumatism and are jointly supporting multiphase development of systemic lupus erythematosus (SLE) classification criteria based on weighted criteria and a continuous probability scale. Prior steps included item generation, item reduction and hierarchical organisation of candidate criteria using an evidence-based approach. Our objectives were to determine relative weights using multicriteria decision analysis (MCDA) and to set a provisional threshold score for SLE classification. An SLE Expert Panel (8 European, 9 North American) submitted 164 real, unique cases with a wide range of SLE probability in a standardised format. Using the candidate criteria, experts scored and rank-ordered 20 representative cases. At an in-person meeting, experts reviewed inter-rater reliability of scoring, further refined criteria definitions and participated in an MCDA exercise. Based on expert consensus decisions on pairwise comparisons of criteria, 1000minds software calculated criteria weights and rank-ordered the remaining 144 cases based on their additive scores. The score of the lowest-ranked case for which complete expert consensus was achieved defined the provisional threshold classification score. Inter-rater reliability of scoring cases with the candidate criteria was good. MCDA involved 74 pairwise decisions and was repeated for the arthritis and mucocutaneous domains when the initial ranking of some cases did not match expert opinion. After criteria weights and additive scores were recalculated once, experts reached consensus for SLE classification for all cases scoring>83. Using an iterative process, the candidate criteria definitions were refined, preliminary weights were calculated and a provisional threshold score for SLE classification was determined.

Most knowledge of fibromyalgia comes from the clinical setting, where healthcare-seeking behavior and selection issues influence study results. The characteristics of fibromyalgia in the general population have not been studied in detail. We developed and tested surrogate study specific criteria for fibromyalgia in rheumatology practices using variables from the US National Health Interview Survey (NHIS) and the modification (for surveys) of the 2010 American College of Rheumatology (ACR) preliminary fibromyalgia criteria. The surrogate criteria were applied to the 2012 NHIS and identified persons who satisfied criteria from symptom data. The NHIS weighted sample of 8446 persons represents 225.7 million US adults. Fibromyalgia was identified in 1.75% (95% CI 1.42, 2.07), or 3.94 million persons. However, 73% of identified cases self-reported a physician's diagnosis other than fibromyalgia. Identified cases had high levels of self-reported pain, non-pain symptoms, comorbidity, psychological distress, medical costs, Social Security and work disability. Caseness was associated with gender, education, ethnicity, citizenship and unhealthy behaviors. Demographics, behaviors, and comorbidity were predictive of case status. Examination of the surrogate polysymptomatic distress scale (PSD) of the 2010 ACR criteria found fibromyalgia symptoms extending through the full length of the scale. Persons identified with criteria-based fibromyalgia have severe symptoms, but most (73%) have not received a clinical diagnosis of fibromyalgia. The association of fibromyalgia-like symptoms over the full length of the PSD scale with physiological as well as mental stressors suggests PSD may be a universal response variable rather than one restricted to fibromyalgia.

Rheumatic and musculoskeletal diseases (RMDs) represent a multitude of degenerative, inflammatory and auto-immune conditions affecting millions of people worldwide. Persons with these diseases may potentially experience severe chronic pain, joint damage, increasing disability and even death. With an increasingly ageing population, the prevalence and burden of RMDs are predicted to increase, placing greater demands on the global practice of rheumatology and related healthcare budgets. Effective treatment of RMDs currently faces a number of challenges in both the developed and developing world, and individual countries may face more specific local challenges. However, limited understanding of the burden of RMDs amongst public health professionals and policy-makers means that these diseases are often not considered a public health priority. The objective of this review is to increase awareness of the RMDs and to identify opportunities to address RMD challenges on both a local and global scale. On 26 September 2014, rheumatology experts from five different continents met at the World Forum on Rheumatic and Musculoskeletal Diseases (WFRMD) to discuss and identify some key challenges for the RMDs community today. The outcomes are presented in this review, focusing on access to rheumatology services, diagnostics and therapies, rheumatology education and training and on clinical trials, as well as investigator-initiated and epidemiological research. The long-term vision of the WFRMD is to increase perception of the RMDs as a major burden to society and to explore potential opportunities to improve global and local RMD care.

Hemophagocytic syndrome (HPS) or hemophagocytic lymphohistiocytosis (HLH) is an acute and rapidly progressive systemic inflammatory disorder characterized by cytopenia, excessive cytokine production, and hyperferritinemia. Common clinical manifestations of HLH are acute unremitting fever, lymphadenopathy, hepatosplenomegaly, and multiorgan failure. Due to a massive cytokine release, this clinical condition is considered as a cytokine storm syndrome. HPS has primary and acquired (secondary, reactive) forms. Its primary form is mostly seen in childhood and caused by various mutations with genetic inheritance and, therefore, is called familial HLH. Secondary HLH may be caused in the presence of an underlying disorder, that is, secondary to a malignant, infectious, or autoimmune/autoinflammatory stimulus. This paper aims to review the pathogenesis and the clinical picture of HLH, and its severe complication, the cytokine storm, with a special emphasis on the developed classification criteria sets for rheumatologists, since COVID-19 infection has clinical symptoms resembling those of the common rheumatologic conditions and possibly triggers HLH. MED-LINE/Pubmed was searched from inception to April 2020, and the following terms were used for data searching: “hemophagocytic syndrome” OR “macrophage activation syndrome” OR “hemophagocytic lymphohistiocytosis”, OR “cytokine storm”. Finally, AND “COVID-19” was included in this algorithm. The selection is restricted to the past 5 years and limited numbers of earlier key references were manually selected. Only full-text manuscripts, published in an English language peer-reviewed journal were included. Manuscript selection procedure and numbers are given in Fig. 2. Briefly, the database search with the following terms of “Hemophagocytic syndrome” OR “Macrophage activation syndrome” OR “Hemophagocytic lymphohistiocytosis” OR “Cytokine storm” yielded 6744 results from inception to April 2020. The selection is restricted to the past 5 years and only limited numbers of earlier key references were selected, and this algorithm resulted in 3080 manuscripts. The addition of (AND “COVID-19”) resulted in 115 publications of which 47 studies, together with four sections of an online book were used in the final review. No statistical method was used. HLH is triggered by genetic conditions, infections, malignancies, autoimmune-autoinflammatory diseases, and some drugs. In COVID-19 patients, secondary HLH and cytokine storm may be responsible for unexplained progressive fever, cytopenia, ARDS, neurological and renal impairment. Differentiation between the primary and secondary forms of HLH is utterly important, since primary form of HLH requires complicated treatments such as hematopoietic stem cell transplantation. Further studies addressing the performance of HScore and other recommendations in the classification of these patients is necessary.