Knevel Lab

Knevel Lab

Data Science lab of the LUMC Rheumatology department

Publications

Highlighted publications

You can also find our articles on PubMed.

Rheumatoid arthritis susceptibility genes show pathotype-specific expression in synovial tissue of patients with early treatment-naïve RA.

Published in Ann Rheum Dis, 2026

Rheumatoid arthritis (RA) exhibits clinical and biological heterogeneity, with synovial tissue stratified into histological pathotypes: lympho-myeloid, diffuse-myeloid, and pauci-immune fibroid. Although genome-wide association studies (GWAS) have uncovered RA risk loci, how genetic risk relates to synovial immunopathology remains unclear. To better understand how genetic predisposition may shape divergent early disease mechanisms, we characterised the expression patterns of GWAS-identified RA susceptibility genes and related rheumatic diseases across the synovial pathotypes. Synovial RNA sequencing of patients with early RA (Pathobiology of Early Arthritis Cohort [PEAC] [N = 87] and Flinders [N = 18]) was used for differential gene expression between pathotypes, and pathway enrichment analyses were performed using GWAS-identified susceptibility genes for RA, osteoarthritis (OA), ankylosing spondylitis, psoriatic arthritis, and systemic lupus erythematosus. RA susceptibility gene expression in synovial tissue separated patients by pathotype and correlated with markers of disease activity. RA susceptibility genes were significantly enriched among genes upregulated in lympho-myeloid synovium and linked to lymphocyte activation and differentiation pathways. In contrast, OA susceptibility genes were upregulated in diffuse-myeloid and fibroid synovium. Both patterns were most pronounced in anticitrullinated protein antibody (ACPA)-positive and directionally consistent in ACPA-negative patients. Expression of RA susceptibility genes is not evenly distributed across synovial pathotypes but is strongly biased towards the lympho-myeloid pathotype, indicating that current GWAS signals preferentially capture immune-driven disease mechanisms. Enrichment of OA susceptibility genes in diffuse-myeloid and fibroid pathotypes, even among ACPA-positive patients, suggests shared biological features between autoimmune and noninflammatory degenerative joint diseases in certain RA subtypes. Synovial pathotype stratification is therefore essential for interpreting genetic risk and understanding disease heterogeneity.

Recommended citation: den Hond IC, Reinders MJT, Lewis MJ, Rivellese F, Pitzalis C, Wong SW, Wechalekar MD, Knevel R, van den Akker EB. (2026) "Rheumatoid arthritis susceptibility genes show pathotype-specific expression in synovial tissue of patients with early treatment-naïve RA." Ann Rheum Dis. doi: 10.1016/j.ard.2026.06.032.
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How do general practitioners diagnose and refer potential rheumatic musculoskeletal complaints? A scoping review.

Published in Clin Rheumatol, 2026

Timely diagnosis and referral of rheumatic and musculoskeletal diseases (RMDs) remain challenging in primary care, with substantial diagnostic delays and a high proportion of rheumatology referrals involving patients without inflammatory rheumatic disease. To examine the diagnostic trajectory of patients presenting with RMD-related complaints, we conducted a scoping review. We defined the diagnostic trajectory as the sequence of diagnostic considerations, investigations, management decisions, and referrals from first presentation to diagnosis or specialist referral. Across 47 included studies, early presentations were heterogeneous and non-specific, often leading to repeated consultations and diagnostic revisions. The underlying condition was frequently not suspected initially, requiring multiple visits before it was considered. General practitioners demonstrated reasonable knowledge of inflammatory features, but documentation of these features in routine electronic health records was often incomplete. Laboratory and imaging investigations were widely used and strongly influenced decision-making, functioning as objective gatekeeping tools for referral despite limited diagnostic yield. Marked variation was found between countries in referral patterns and investigations used, suggesting an important role for healthcare system structure in shaping diagnostic trajectories. The evidence base was constrained by predominantly narrow disease-specific populations and few studies capturing the full diagnostic pathway from primary care presentation to specialist diagnosis.Overall, our findings indicate that delayed diagnosis of RMDs reflects knowledge gaps, the ambiguity of early disease, and reliance on objective investigations. Efforts to improve clinical decision-making for early diagnosis and timely referral require consideration of the non-specific, early-stage nature of RMDs in primary care, longitudinal clinical information, and differences between healthcare systems.

Recommended citation: Gomon G, Otón T, Carmona L, le Cessie S, Knevel R. (2026) "How do general practitioners diagnose and refer potential rheumatic musculoskeletal complaints? A scoping review." Clin Rheumatol. doi: 10.1007/s10067-026-08282-w.
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Hand-dominant joint involvement pattern associates with favourable, and polyarthritis with unfavourable, treatment response to both csDMARDs and bDMARDs in early rheumatoid arthritis: a combined analysis of NORD-STAR and BeSt trials.

Published in Ann Rheum Dis, 2026

To investigate the association between joint involvement pattern (JIP) subgroups and treatment responses to conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) and biological disease-modifying antirheumatic drugs (bDMARDs), and to compare the impact of JIP subgroups with other clinical parameters in treatment-naïve patients with early rheumatoid arthritis (RA). An individual patient data meta-analysis was conducted using 2 randomised controlled trials, NOrdic Rheumatic Diseases Strategy Trials And Registries (NORD-STAR) and Behandel-Strategieën (BeSt), including 1250 treatment-naïve patients with early RA. JIP subgroup assignment was based on 4 previously identified subgroups defined by baseline clinical characteristics, primarily joint involvement in the 66/68 joint scheme. Treatment outcomes were measured using the longitudinal Clinical Disease Activity Index (CDAI) and other disease activity indices through week 48. Associations of the JIP subgroups and other clinical predictors were evaluated using a mixed-model analysis. Patients with a hand-dominant JIP (JIP-Hand) showed significantly better CDAI scores after treatment (Beta for CDAI = -1.4 [95% CI, -2.3 to -0.55]; p = .0016), whereas those with a polyarthritis pattern (JIP-Poly) exhibited worse outcomes (Beta = 0.95 [95% CI, 0.064-1.8]; p = .035). Female sex was also associated with worse CDAI scores (Beta = 1.2 [95% CI, 0.40-2.0]; p = .0031), whereas anticitrullinated protein antibodies did not show a significant association (Beta = 0.19 [95% CI, -0.69 to 1.1]; p = .67). When compared across groups, csDMARDs and combined bDMARDs were similarly effective in the respective JIP subgroups (interaction p > .10). In early RA, csDMARD and bDMARD treatments resulted in the greatest improvement in disease activity in JIP-Hand and the least improvement in JIP-Poly.

Recommended citation: Nagafuchi Y, Maarseveen TD, Lend K, Rudin A, Gudbjornsson B, Nordström D, Haavardsholm EA, Gröndal G, Lampa J, Petersen KH, Heiberg MS, Hetland ML, Nurmohamed M, Østergaard M, van Vollenhoven R, Uhlig T, Sokka-Isler T, van den Akker EB, Huizinga TWJ, Bergstra SA, Knevel R. (2026) "Hand-dominant joint involvement pattern associates with favourable, and polyarthritis with unfavourable, treatment response to both csDMARDs and bDMARDs in early rheumatoid arthritis: a combined analysis of NORD-STAR and BeSt trials." Ann Rheum Dis. doi: 10.1016/j.ard.2026.02.005.
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Referral pathways and duration of care for musculoskeletal complaints across Europe: an analysis of primary and secondary care.

Published in Ann Rheum Dis, 2026

The objective of the study is to compare care pathways of patients with musculoskeletal (MSK) complaints-from first presentation in primary care to referral and follow-up in rheumatology-across 5 European healthcare systems, and to explore how healthcare system characteristics influence these pathways. Routinely collected healthcare data from 5 European countries (UK, Sweden, the Netherlands, Spain, and Hungary) were analysed. Primary care data included > 4 million adults with at least 1 MSK encounter, and secondary rheumatology data included > 600,000 patients. Primary care consultation rates, referral rates to specialist care, and rheumatology follow-up duration were compared across countries. Healthcare characteristics were extracted from the literature. The distribution of MSK complaints in primary care was similar across countries, with 25% to 30% of residents visiting their general practitioner annually for an MSK complaint (UK data not available). In contrast, referral of such patients with MSK complaints to rheumatology varied considerably (5%-38%). Among those referred, 46% to 70% were discharged within 3 months, whereas only 13% to 43% remained in long-term rheumatology care. We observed that countries with a high proportion of sustained long-term rheumatology care (UK and Sweden) had lower referral rates, fewer rheumatologists per capita, and employed a selective triaging system, whereas countries where referrals more frequently resulted in short-term rheumatology care (the Netherlands, Spain, and Hungary) had higher referral rates and employed nonselective triaging. Substantial cross-country variation exists in the management of MSK complaints. Although primary care MSK presentations are similar, referral rates and the patient-mix reaching rheumatology differ widely between countries-an important consideration for developing cross-national clinical guidelines and diagnostic tools.

Recommended citation: Gomon G, Raffray M, Betancort Rodríguez C, Misák Á, Struik L, le Roux P, Perez-Sancristobal I, Curiel Manzanas S, Polentinos-Castro E, Del Cura González MI, Kováts T, Prieto-Alhambra D, Mook-Kanamori D, Westerlind H, Majnik J, Nagy G, Pratt A, Schiphof D, Rodriguez-Rodriguez L, le Cessie S, Askling J, Knevel R. (2026) "Referral pathways and duration of care for musculoskeletal complaints across Europe: an analysis of primary and secondary care." Ann Rheum Dis. doi: 10.1016/j.ard.2026.05.011.
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The journey of Europeans with musculoskeletal complaints: the creation of the SPIDeRR’s personas.

Published in EULAR Rheumatol Open, 2026

The Stratification of Patients Using Advanced Integrative Modelling of Data Routinely Acquired for Diagnosing Rheumatic Complaints (SPIDeRR) project aims to improve the patient journey for individuals with musculoskeletal (MSK) complaints due to rheumatic and musculoskeletal diseases (RMDs). The primary objective was to understand patients’ experiences navigating the healthcare system to achieve timely diagnosis and treatment for RMDs. Secondary objectives included identifying challenges and opportunities for implementing digital tools for help seeking and diagnosis, thus enhancing access to appropriate treatments. Based on the patient experience mapping framework, 3 substudies were conducted as follows: (i) a systematic review and stakeholder surveys to identify key stages and touchpoints; (ii) focus groups to gather additional insights; and (iii) synthesis of findings into visual maps and personas highlighting gaps and potential solutions. Substudy 1 (36 studies and 247 survey participants) revealed that navigating the healthcare systems in Europe is complex, facing significant barriers, such as limited specialist access, knowledge gaps, and inconsistent treatment pathways for people with RMDs. Substudy 2 (28 participants with and without RMDs) found that initial symptom management may delay proper care, multiple emotions emerge while waiting for a solution, and preferences for direct specialist access vs general practitioner gatekeeping vary depending on individual and healthcare system. Substudy 3 developed visual representations of 5 evocative patient journeys, outlining stages, obstacles, interactions, and emotions. The journey of Europeans with MSK complaints is intricate and country specific, posing challenges for nontailored solutions. Personalised digital tools, improved healthcare provider education, and efficient communication between care levels are recommended to enhance the patient experience and improve outcomes for individuals with RMDs.

Recommended citation: Otón T, Muehlensiepen F, Knevel R, Villalobos-Quesada MJ, Axnäs BB, Morf H, Stratingh K, Pérez M, Loza E, Carmona L. (2026) "The journey of Europeans with musculoskeletal complaints: the creation of the SPIDeRR's personas." EULAR Rheumatol Open. doi: 10.1016/j.ero.2026.100177.
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Rheumatic Digital Twin: Proposed Machine Learning-Based Multimodal Framework to Inform Clinical Decision-Making.

Published in J Med Internet Res, 2026

Rheumatic diseases are chronic, immune-mediated conditions characterized by significant heterogeneity in presentation and disease course. However, current clinical approaches often rely on snapshot-based assessments that fail to capture the complex longitudinal evolution of these conditions. To address these limitations and support the implementation of precision medicine, we present the design for the Rheumatic Digital Twin, a novel, modular conceptual framework intended to integrate heterogeneous multimodal data, ranging from electronic health records and clinical notes to imaging and omics, into a dynamic, computational representation of the patient journey. Our theoretical architecture addresses challenges related to data silos and variable availability of data modalities through a multistage approach that envisions the use of domain-specific foundation models to independently process distinct data modalities. To effectively model the temporal progression inherent in chronic diseases, the proposed design utilizes Transformer architectures, leveraging self-attention mechanisms to treat patient events, such as lab results or medication changes, as sequential data tokens. We describe how these unimodal representations would subsequently be fused via joint embedding techniques to construct a shared, multimodal representational space. Envisioned to function analogously to a recommender system, the Rheumatic Digital Twin framework is modeled to map patients into a latent space where proximity reflects clinical and biological similarity. By identifying “nearest neighbors,” historical patients with comparable trajectories, the system aims to enable in silico cohorting, theoretically allowing clinicians to forecast key clinical events, predict treatment responses, and identify likely disease courses based on the outcomes of similar peers.

Recommended citation: Selani D, Knevel R, Reinders M, van den Akker EB. (2026) "Rheumatic Digital Twin: Proposed Machine Learning-Based Multimodal Framework to Inform Clinical Decision-Making." J Med Internet Res. doi: 10.2196/86763.
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Work smarter, not harder: achieve expert-level diagnosis extraction from medical records with optimal prompting of large language models.

Published in Ann Rheum Dis, 2026

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Recommended citation: Maarseveen TD, Selani D, Steinz N, Ten Brinck R, Glas HK, Veris-van Dieren J, Reinders MJT, van den Akker EB, Knevel R. (2026) "Work smarter, not harder: achieve expert-level diagnosis extraction from medical records with optimal prompting of large language models." Ann Rheum Dis. doi: 10.1016/j.ard.2025.11.001.
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Methods for Prioritizing Causal Genes in Molecular Studies of Human Disease: The State of the Art.

Published in Genet Epidemiol, 2026

In the last decade, genome-wide association studies (GWAS) have identified tens of thousands of common variants associated with a wide array of complex traits and diseases. Integration of GWAS with molecular data has informed the development of statistical tools for causal gene discovery. In this paper, we give an overview of commonly used causal inference methods and discuss the strengths and limitations of colocalization, Mendelian randomization (MR) and network-based approaches. Colocalization is often used to assess whether the genetic association signals for two traits arise from the same causal variant, thereby strengthening inferred causal associations. MR was developed to tackle issues of confounding and reverse causality, providing a rigorous approach to causal inference and demonstrating improved false discovery rates. Unlike MR, network-based analyses employ a discovery approach and model complex relationships between multiple variables. All causal inference methods are, to varying degrees, susceptible to spurious associations due to genetic confounding, pleiotropy and linkage disequilibrium. Here, we discuss the latest developments in the field of causal gene inference and limitations of these methods. We give an overview of interplay between different approaches as well as practical applications with reference to published examples in context of heart disease.

Recommended citation: Patasova K, Sedaghati-Khayat B, Knevel R, Cordell HJ, Pratt AG. (2026) "Methods for Prioritizing Causal Genes in Molecular Studies of Human Disease: The State of the Art." Genet Epidemiol. doi: 10.1002/gepi.70037.
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Exploring the optimal follow-up for systemic sclerosis patients: study protocol for a Dutch multicenter randomized controlled trial.

Published in Trials, 2026

Currently, evidence-based guidelines for the frequency and intensity of follow-up of systemic sclerosis (SSc) patients are not available. Based on expert opinion, an annual extensive evaluation is recommended. A multidisciplinary Care Pathway that integrates this annual extensive evaluation at the Leiden University Medical Center has shown increased patient satisfaction, decreased healthcare utilization, and improved outcomes in SSc patients (1, 2). However, for a subgroup of SSc patients with relatively mild disease, this annual extensive evaluation might be redundant. Therefore, this study aims to evaluate whether assessment in a regular outpatient clinic setting is an acceptable alternative to extensive annual evaluation in the Care Pathway in SSc patients with a low risk of disease progression. This study is designed as a multicenter (n = 3) non-inferiority randomized controlled trial. SSc patients are categorized into three categories for risk of disease progression (low, intermediate, or high) based on a previously published risk prediction model (3). Patients with a predicted low or intermediate risk of disease progression are randomized between (1) follow-up in the outpatient clinic (intervention) and (2) follow-up via usual care according to the annual Care Pathway (control group). The year after the “study visit,” all patients are evaluated in the Care Pathway. In this study, 250 patients will be recruited and randomized. The primary outcome is healthcare utilization, which will be assessed via questionnaires. Secondary outcome measures include disease progression, patients’ perception of disease and care, and health-related quality of life. Healthcare utilization is defined as the number of contacts with a healthcare professional and will be analyzed using descriptive statistics and linear regression analysis. There is an unmet need for tailor-made care for SSc patients in accordance with disease activity, and evidence-based guidelines regarding the follow-up of SSc patients are lacking. This is the first randomized controlled trial evaluating the optimal follow-up for SSc patients at low risk of disease progression. Results of this study will show whether routine assessment at the outpatient clinic is an acceptable alternative to assessment in a standardized care setting including an annual 6-min walk test, an ECG, lab, mRSS, and a pulmonary function test. ClinicalTrials.gov NCT05103553. Registered on October 11, 2021.

Recommended citation: Hoekstra EM, Liem SIE, Ahmed S, Dijkman LD, van der Wouden KE, van Leeuwen NM, Hortensius-Varkevisser AM, van der Lans SE, Voorde LJJB, Dongen HG, Knevel R, Huizinga TWJ, Schouffoer AA, de Vries-Bouwstra JK. (2026) "Exploring the optimal follow-up for systemic sclerosis patients: study protocol for a Dutch multicenter randomized controlled trial." Trials. doi: 10.1186/s13063-026-09494-w.
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Attrition and representativeness in development and validation of online symptom checkers-a case study on the Rheumatic? Questionnaire.

Published in Front Artif Intell, 2026

Online symptom checkers are often developed and validated on data subject to self-selection and selective attrition, potentially introducing biases in prediction models. To assess recruitment, selection, and attrition patterns in a large Dutch online symptom checker for musculoskeletal complaints and to evaluate potential biases by comparing participant characteristics across recruitment sources and with external target populations. Using data from the online Dutch Rheumatic ? Questionnaire on musculoskeletal complaints, we compared baseline characteristics and key self-reported symptoms between responders to the follow-up survey and nonresponders. The survey responders were furthermore compared according to source of recruitment to the questionnaire, i.e., via primary care clinics, secondary care clinics, or via different online sources. Sex, age and BMI distributions from the total study group were compared to external data of potential target populations of primary and secondary care patients within the Netherlands. The total study group of answers to the questionnaire comprised 31,457 responders, of which 50% ( n  = 15,591) responded to the follow-up survey. Study participants were predominantly female (76%), middle-aged (one-third 50-60 years), never-smokers (66%), and overweight. While participants recruited through healthcare settings resembled target populations, follow-up survey responders were older, had more rheumatic diagnoses (49% vs. 32%), and reported more symptoms than non-responders. Participant characteristics varied by recruitment source, with social media attracting younger females while healthcare routes reached more diverse populations with varying symptom presentations. Patterns of recruitment and attrition produced differences in participant characteristics. Healthcare-based recruitment yielded participants resembling intended target populations, and follow-up survey responders differed on some points from nonresponders. Awareness of these selection processes is essential when using real-world symptom checker data for model development.

Recommended citation: Zegers FD, Qin L, Selani D, Gomon G, Maarseveen T, Glas K, van Tubergen A, Ruiterman YG, Reinders M, van den Akker E, de Jong CB, Klareskog L, Axnäs B, Bos R, le Cessie S, Knevel R. (2026) "Attrition and representativeness in development and validation of online symptom checkers-a case study on the Rheumatic? Questionnaire." Front Artif Intell. doi: 10.3389/frai.2026.1815241.
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Evaluating the Accuracy of the Frysian Questionnaire for Differentiation of Musculoskeletal Complaints for Triage of Musculoskeletal Diseases: Algorithm Development and Validation Study.

Published in JMIR Med Inform, 2025

Inflammatory rheumatic diseases (IRDs) affect 5% of the general population, whereas 35% of the population experiences musculoskeletal concerns. IRDs cause early disability, reduced life expectancy, and considerable health care costs. Early diagnosis is essential to prevent long-term damage. Similarly important is the early identification of patients with musculoskeletal concerns without IRDs to prevent unnecessary health care expenses. Of the population referred to the rheumatologist, 60% have noninflammatory musculoskeletal concerns, whereas only 20% of patients with an IRD see a rheumatologist within 3 months of symptom onset. The need for digital predictive (triage) tools for rheumatic and musculoskeletal diseases led to the development of the Frysian Questionnaire for Differentiation of Musculoskeletal Complaints (FRYQ). This study aimed to assess whether the FRYQ can distinguish IRD from noninflammatory musculoskeletal concerns in general, and rheumatoid arthritis and fibromyalgia specifically, in newly referred patients. The FRYQ is an 87-item tool (20 open-ended and 67 closed-ended questions) used to triage new rheumatology patients at Frisius Medical Center in the Netherlands. We analyzed data from 2 sources: dataset A with 728 outpatient clinic patients and dataset B with 373 patients from the Joint Pain Assessment Scoring Tool study. We built a classifier using Extreme Gradient Boosting to distinguish inflammatory from noninflammatory conditions based on closed-ended questions. Using elastic net regularization, we identified the most informative questions. We evaluated classification using receiver operating characteristic curve analysis and assessed feature importance through Shapley Additive Explanation analysis. To test generalizability, we replicated our analysis on dataset B. Finally, we examined whether the questions of the FRYQ could be used to identify specific conditions beyond the general categories of IRD and non-IRD, specifically for detecting fibromyalgia and rheumatoid arthritis. Feature selection reduced the questionnaire from 67 to 28 items while maintaining discriminative power. After initial development, the model achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.72 (95% CI 0.67-0.78) for distinguishing inflammatory from noninflammatory conditions in an external validation set. Using a probability threshold of 0.30, the model achieved 71% sensitivity and 56% specificity on external validation. The FRYQ demonstrated stronger performance in identifying specific diagnoses such as fibromyalgia (AUC-ROC=0.81) and rheumatoid arthritis (AUC-ROC=0.77). Key discriminating features included symptom duration, pain response to movement, and anti-inflammatory medication effectiveness. The FRYQ effectively distinguishes inflammatory from noninflammatory rheumatic conditions before specialist consultation and shows particular strength in identifying fibromyalgia and rheumatoid arthritis. This tool could improve rheumatology triage by prioritizing referrals with high likelihood of IRD for early rheumatologist evaluation while directing other patients to appropriate alternative resources. Prospective studies are needed to determine the FRYQ’s impact on clinical outcomes and health care efficiency.

Recommended citation: Maarseveen TD, Reimann F, Al Hasan A, Schilder A, Zhang D, Wink F, Hendriks L, Knevel R, Bos R. (2025) "Evaluating the Accuracy of the Frysian Questionnaire for Differentiation of Musculoskeletal Complaints for Triage of Musculoskeletal Diseases: Algorithm Development and Validation Study." JMIR Med Inform. doi: 10.2196/77345.
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The patient journey in rheumatic and musculoskeletal diseases: a systematic review.

Published in EULAR Rheumatol Open, 2025

To provide a comprehensive understanding of the patient journey experienced by individuals with rheumatic and musculoskeletal diseases (RMDs). We systematically searched 3 medical databases to identify studies that reported patient experiences, challenges and barriers from the perspectives of both the patient and healthcare provider. Inclusion criteria included peer-reviewed original research articles based on qualitative or mixed methods. The quality of the evidence was evaluated using the Joanna Briggs Institute’s (JBI) Critical Appraisal Checklist. Studies were analysed to identify touchpoints (contact of a patient with a healthcare organisation), delays throughout the patient journey, and barriers or challenges. The search identified 1470 records, resulting in the inclusion of 36 studies. According to the JBI checklist, 27 studies were of high or medium-high quality. Eight touchpoints were identified and characterised: (1) awareness, (2) help-seeking, (3) first encounter, (4) clinical suspicion in primary care, (5) diagnostic tests in primary care, (6) management (outside of rheumatology), (7) rheumatology referral and (8) management in rheumatology. Conflicting areas highlight the need for enhanced education for healthcare providers, better coordination of care and a more patient-centred approach to management. The review helped us describe a general patient journey for people with RMDs. Identifying and addressing the conflicting points in the patient journey is essential for improving care and outcomes for individuals with RMDs.

Recommended citation: Otón T, Villalobos-Quesada M, Loza E, Knevel R, Carmona L. (2025) "The patient journey in rheumatic and musculoskeletal diseases: a systematic review." EULAR Rheumatol Open. doi: 10.1016/j.ero.2025.06.010.
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Systematic review and independent validation of genetic factors of radiographic outcome in rheumatoid arthritis identifies a genome-wide association with CARD9

Published in Ann Rheum Dis, 2025

This study aimed to investigate non-HLA genetic mechanisms underlying radiographic severity in rheumatoid arthritis (RA).

Recommended citation: Sharma SD, Hum RM, Nair N, Marshall L, Storrie A, Bowes J, MacGregor A, Yates M, Morris AP, Verstappen S, Barton A, van Steenbergen H, Knevel R, van der Helm-van Mil A, Viatte S. (2025) "Systematic review and independent validation of genetic factors of radiographic outcome in rheumatoid arthritis identifies a genome-wide association with CARD9" Ann Rheum Dis. 2025 Sep;84(9):1469-1483. doi: 10.1016/j.ard.2025.04.007. Epub 2025 May 8.
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Time-independent disease state identification defines distinct trajectories determined by localised vs systemic inflammation in patients with early rheumatoid arthritis

Published in Ann Rheum Dis, 2025

Patients with rheumatoid arthritis (RA) display different trajectories towards improvement of disease. We aimed to disentangle the heterogeneity of RA disease trajectories from the first clinical visit onwards using graph-based pseudotime analysis.

Recommended citation: Steinz N, Maarseveen TD, van den Akker EB, Cope AP, Isaacs JD, Winkler AR, Huizinga TWJ, Abraham Y, Knevel R. (2025) "Time-independent disease state identification defines distinct trajectories determined by localised vs systemic inflammation in patients with early rheumatoid arthritis" Ann Rheum Dis. 2025 Aug;84(8):1301-1312. doi: 10.1016/j.ard.2025.04.011. Epub 2025 May 9.
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Rheumatoid arthritis-associated interstitial lung disease in countries across the world

Published in Semin Arthritis Rheum, 2025

We aimed to describe the incidence of RA-ILD in various countries worldwide, and to explore its association with RA disease activity.

Recommended citation: Heckert SL, Maarseveen TD, Marges ER, Chopra A, Vega-Morales D, Toit RD, Winchow LL, Govind N, Toro-Gutiérrez CE, Knevel R, van der Helm-van Mil AH, Huizinga TW, Allaart CF, Bergstra SA. (2025) "Rheumatoid arthritis-associated interstitial lung disease in countries across the world" Semin Arthritis Rheum. 2025 Aug;73:152719. doi: 10.1016/j.semarthrit.2025.152719. Epub 2025 Apr 12.
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Post-translationally modified proteins bind and activate complement with implications for cellular uptake and autoantibody formation

Published in J Autoimmun, 2025

Autoimmune diseases, such as rheumatoid arthritis (RA), are characterized by the presence of autoantibodies including those targeting self-proteins modified by post-translational modifications (PTMs). The complement system is known for its role in innate immune defense, but also in clearing debris and induction of antibody responses. We therefore hypothesized that complement could directly bind to PTMs and target PTM-modified proteins for clearance, or stimulate (chronic) inflammation and development of anti-PTM autoimmunity.

Recommended citation: van den Beukel MD, Zhang L, van der Meulen S, Borggreven NV, Nugteren S, Brouwer MC, Pouw RB, Gelderman KA, de Ru AH, Janssen GMC, van Veelen PA, Knevel R, Parren PWHI, Trouw LA. (2025) "Post-translationally modified proteins bind and activate complement with implications for cellular uptake and autoantibody formation" J Autoimmun. 2025 Jul;155:103444. doi: 10.1016/j.jaut.2025.103444. Epub 2025 Jun 23.
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Let’s ask the patient: disease prediction based on patients’ symptom descriptions in free text

Published in Rheumatol Adv Pract, 2025

This study evaluates the value self-reported free-text symptom descriptions for supporting diagnostic decisions in osteoarthritis (OA), fibromyalgia (FM) and immune-mediated rheumatic diseases (imRD) using natural language processing (NLP) and machine learning (ML).

Recommended citation: Pérez-Sancristóbal I, Steinz N, Qin L, Maarseveen T, Zegers F, Bislawska Axnäs B, Rodríguez-Rodríguez L, Knevel R. (2025) "Let's ask the patient: disease prediction based on patients' symptom descriptions in free text" Rheumatol Adv Pract. 2025 Sep 10;9(4):rkaf103. doi: 10.1093/rap/rkaf103. eCollection 2025.
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Location and amount of joint involvement differentiates rheumatoid arthritis into different clinical subsets

Published in NPJ Digit Med, 2025

Rheumatoid arthritis (RA) is a heterogeneous disease with variable symptoms, prognosis, and treatment response, necessitating refined patient classification. We applied multimodal deep learning and clustering to identify distinct RA phenotypes using baseline clinical data from 1,387 patients in the Leiden Rheumatology clinic. Four Joint Involvement Patterns (JIP) emerged: foot-predominant arthritis, seropositive oligoarticular disease, seronegative hand arthritis, and polyarthritis. Findings were validated in clinical trial data (n = 307) and an independent secondary care cohort (n = 515). Clusters showed high stability and significant differences in remission rates (P = 0.007) and methotrexate failure (P < 0.001). JIP-hand patients had superior outcomes (particularly in ACPA-positive patients) versus JIP-foot (HR:0.37, P < 0.001) and JIP-poly (HR:0.33, P = 0.005), independent of baseline disease activity and clinical markers. Synovial histology analysis (n = 194) revealed distinct inflammatory patterns across clusters, hinting at different underlying biological mechanisms. These validated RA phenotypes based on joint involvement patterns may enable targeted research into disease mechanisms and personalized treatment strategies.

Recommended citation: Maarseveen TD, Maurits MP, Coletto LA, Perniola S, Böhringer S, Steinz N, Bergstra SA, Bruno D, Gigante MR, Pacucci VA, Petricca L, Boxma-de Klerk B, Glas HK, Di Mario C, Campobasso D, Tolusso B, Veris-van Dieren J, van der Helm-van Mil AHM, Gremese E, D'Agostino MA, Reinders MJT, Gessi M, Huizinga TWJ, Alivernini S, van den Akker EB, Knevel R. (2025) "Location and amount of joint involvement differentiates rheumatoid arthritis into different clinical subsets" NPJ Digit Med. 2025 Oct 23;8(1):623. doi: 10.1038/s41746-025-01997-1.
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Rheumatic? A diagnostic decision support tool for individuals suspecting rheumatic diseases: Mixed-methods usability and acceptability study

Published in BMC Rheumatol, 2025

The early diagnosis of inflammatory rheumatic diseases (IRDs) is of paramount importance in order to prevent irreversible damage to joints and to optimize treatment outcomes. Nevertheless, conventional care pathways frequently entail diagnostic delays spanning several months. Symptom checkers (SCs) have the potential to provide a solution by offering validated symptom assessments, improving triage systems and expediting diagnostic evaluations. The objective of this mixed-methods study is to assess the usability and acceptability of the SC Rheumatic? among individuals with suspected rheumatic diseases.

Recommended citation: Jakobi S, Boy K, Wagner M, May S, Temiz A, Liphardt AM, Araujo E, Carmona L, Knevel R, Schett G, Knitza J, Muehlensiepen F, Morf H. (2025) "Rheumatic? A diagnostic decision support tool for individuals suspecting rheumatic diseases: Mixed-methods usability and acceptability study" BMC Rheumatol. 2025 May 23;9(1):59. doi: 10.1186/s41927-025-00507-w.
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Autoantibody clusters in rheumatoid arthritis are not driven by antigen specificity or isotype

Published in RMD Open, 2025

Autoantibodies are a key feature of rheumatoid arthritis (RA). They can be detected years before disease onset, but it is unknown if there is any pattern in the co-occurrence of antigen recognition or isotype profiles. A common signature could point to a unique initial trigger for autoantibody development. Therefore, we sought to determine if there is a pattern in antigen or isotype reactivity in pre-symptomatic cases and established RA.

Recommended citation: van Mourik AG, Johansson L, van Wesemael TJ, Maurits MP, Kokkonen H, Rönnelid J, Knevel R, Toes REM, Rantapää-Dahlqvist S, van der Woude D. (2025) "Autoantibody clusters in rheumatoid arthritis are not driven by antigen specificity or isotype" RMD Open. 2025 Jun 13;11(2):e005291. doi: 10.1136/rmdopen-2024-005291.
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Improving musculoskeletal care with AI enhanced triage through data driven screening of referral letters

Published in NPJ Digit Med, 2025

Musculoskeletal complaints account for 30% of GP consultations, with many referred to rheumatology clinics via letters. This study developed a Machine Learning (ML) pipeline to prioritize referrals by identifying rheumatoid arthritis (RA), osteoarthritis, fibromyalgia, and patients requiring long-term care. Using 8044 referral letters from 5728 patients across 12 clinics, we trained and validated ML models in two large centers and tested their generalizability in the remaining ten. The models were robust, with RA achieving an AUC-ROC of 0.78 (CI: 0.74-0.83), osteoarthritis 0.71 (CI: 0.67-0.74), fibromyalgia 0.81 (CI: 0.77-0.85), and chronic follow-up 0.63 (CI: 0.61-0.66). The RA-classifier outperformed manual referral systems, as it prioritised RA over non-RA cases (P < 0.001), while the manual referral system could not differentiate between the two. The other classifiers showed similar prioritisation improvements, highlighting the potential to enhance care efficiency, reduce clinician workload, and facilitate earlier specialized care. Future work will focus on building clinical decision-support tools.

Recommended citation: Maarseveen TD, Glas HK, Veris-van Dieren J, van den Akker E, Knevel R. (2025) "Improving musculoskeletal care with AI enhanced triage through data driven screening of referral letters" NPJ Digit Med. 2025 Feb 14;8(1):98. doi: 10.1038/s41746-025-01495-4.
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The journey of patients with musculoskeletal complaints in Europe: a cross-sectional European survey

Published in Rheumatol Int, 2025

Rheumatic and musculoskeletal diseases (RMDs) are highly prevalent and place a significant socioeconomic burden on healthcare systems. However, their diagnosis and management remain suboptimal. This study aimed to analyze healthcare-seeking behaviors, key touchpoints, access barriers, and diagnostic pathways for individuals experiencing initial or progressive symptoms of RMDs across European countries. Understanding these differences is crucial for improving early access to specialized care. A cross-sectional online survey was conducted with 141 participants from seven European countries, including 67 rheumatologists and 39 general practitioners (GPs). The survey assessed initial healthcare-seeking behaviors, delays in diagnosis, and perceived barriers to specialized rheumatology care. Descriptive and inferential statistical methods were used for data analysis. The survey indicated that individuals experiencing RMD symptoms primarily seek information through internet research and GP consultations. Despite their role as primary gatekeepers, GPs’ knowledge of RMDs was generally perceived as moderate to low. Significant disparities in access to rheumatological diagnostics, time to diagnosis, and treatment, coupled with organizational barriers between primary and specialist care, were reported across most countries. Spanish participants reported the longest diagnostic delays, while Swedish respondents experienced the shortest. Additionally, access to sacroiliac MRI was limited in Hungary and Spain, whereas glucocorticoids were widely available across all countries according to the participants. The study also revealed that early arthritis clinics were most accessible in the UK from the participants’ perspectives. Significant variations in healthcare access for patients with RMDs persist across Europe. Strategies to enhance early detection, including GP education and improved specialist accessibility, are essential to optimizing patient outcomes.

Recommended citation: Wagner M, Otón T, Muehlensiepen F, Stratingh K, Loza E, Knevel R, Carmona L. (2025) "The journey of patients with musculoskeletal complaints in Europe: a cross-sectional European survey" Rheumatol Int. 2025 Apr 18;45(5):107. doi: 10.1007/s00296-025-05863-x.
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Finding the Right Fit for Genes in Rheumatology Clinical Care

Published in Arthritis Rheumatol, 2024

DOI: 10.1002/art.42769PMID: 38057135 [Indexed for MEDLINE]

Recommended citation: Vassy JL, Knevel R, Liao KP. (2024) "Finding the Right Fit for Genes in Rheumatology Clinical Care" Arthritis Rheumatol. 2024 May;76(5):675-676. doi: 10.1002/art.42769. Epub 2024 Jan 9.
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Is glucocorticoid bridging therapy associated with later use of glucocorticoids and biological DMARDs during the disease course of patients with rheumatoid arthritis in daily practice? A real-world data analysis

Published in Semin Arthritis Rheum, 2024

To evaluate if initially starting glucocorticoid (GC) bridging leads to a higher probability of long-term GC and biological (b)DMARD use in rheumatoid arthritis (RA)-patients.

Recommended citation: van Ouwerkerk L, Bergstra SA, Maarseveen TD, Huizinga TWJ, Knevel R, Allaart CF. (2024) "Is glucocorticoid bridging therapy associated with later use of glucocorticoids and biological DMARDs during the disease course of patients with rheumatoid arthritis in daily practice? A real-world data analysis" Semin Arthritis Rheum. 2024 Feb;64:152305. doi: 10.1016/j.semarthrit.2023.152305. Epub 2023 Nov 10.
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RPA3-UMAD1 rs12702634 and rheumatoid arthritis-associated interstitial lung disease in European ancestry

Published in Rheumatol Adv Pract, 2024

Recently, a genome-wide association study identified an association between RA-associated interstitial lung disease (ILD) and RPA3-UMAD1 rs12702634 in the Japanese population, especially for patients with a usual interstitial pneumonia (UIP) pattern. We aimed to replicate this association in a European population and test for interaction with MUC5B rs35705950.

Recommended citation: Juge PA, Sparks JA, Gazal S, Ebstein E, Borie R, Debray MP, Kannengiesser C, McDermott GC, Cui J, Hayashi K, Doyle TJ, van Moorsel CHM, van der Vis JJ, Grutters JC, Knevel R, Heckert SL, Vasarmidi E, Antoniou KM, van der Helm van Mil AHM, Boileau C, Crestani B, Dieudé P. (2024) "RPA3-UMAD1 rs12702634 and rheumatoid arthritis-associated interstitial lung disease in European ancestry" Rheumatol Adv Pract. 2024 Jun 4;8(2):rkae059. doi: 10.1093/rap/rkae059. eCollection 2024.
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Using an artificial intelligence tool incorporating natural language processing to identify patients with a diagnosis of ANCA-associated vasculitis in electronic health records

Published in Comput Biol Med, 2024

Because anti-neutrophil cytoplasmatic antibody (ANCA)-associated vasculitis (AAV) is a rare, life-threatening, auto-immune disease, conducting research is difficult but essential. A long-lasting challenge is to identify rare AAV patients within the electronic-health-record (EHR)-system to facilitate real-world research. Artificial intelligence (AI)-search tools using natural language processing (NLP) for text-mining are increasingly postulated as a solution.

Recommended citation: van Leeuwen JR, Penne EL, Rabelink T, Knevel R, Teng YKO. (2024) "Using an artificial intelligence tool incorporating natural language processing to identify patients with a diagnosis of ANCA-associated vasculitis in electronic health records" Comput Biol Med. 2024 Jan;168:107757. doi: 10.1016/j.compbiomed.2023.107757. Epub 2023 Nov 25.
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Rapid Response to Remdesivir in Hospitalised COVID-19 Patients: A Propensity Score Weighted Multicentre Cohort Study

Published in Infect Dis Ther, 2023

Remdesivir is a registered treatment for hospitalised patients with COVID-19 that has moderate clinical effectiveness. Anecdotally, some patients’ respiratory insufficiency seemed to recover particularly rapidly after initiation of remdesivir. In this study, we investigated if this rapid improvement was caused by remdesivir, and which patient characteristics might predict a rapid clinical improvement in response to remdesivir.

Recommended citation: Leegwater E, Dol L, Benard MR, Roelofsen EE, Delfos NM, van der Feltz M, Mollema FPN, Bosma LBE, Visser LE, Ottens TH, van Burgel ND, Arbous SM, El Bouazzaoui LH, Knevel R, Groenwold RHH, de Boer MGJ, Visser LG, Rosendaal FR, Wilms EB, van Nieuwkoop C. (2023) "Rapid Response to Remdesivir in Hospitalised COVID-19 Patients: A Propensity Score Weighted Multicentre Cohort Study" Infect Dis Ther. 2023 Oct;12(10):2471-2484. doi: 10.1007/s40121-023-00874-2. Epub 2023 Oct 6.
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Population-based user-perceived experience of Rheumatic?: a novel digital symptom-checker in rheumatology

Published in RMD Open, 2023

Digital symptom-checkers (SCs) have potential to improve rheumatology triage and reduce diagnostic delays. In addition to being accurate, SCs should be user friendly and meet patient’s needs. Here, we examined usability and acceptance of Rheumatic?-a new and freely available online SC (currently with >44 000 users)-in a real-world setting.

Recommended citation: Lundberg K, Qin L, Aulin C, van Spil WE, Maurits MP, Knevel R. (2023) "Population-based user-perceived experience of Rheumatic?: a novel digital symptom-checker in rheumatology" RMD Open. 2023 Apr;9(2):e002974. doi: 10.1136/rmdopen-2022-002974.
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From real-world electronic health record data to real-world results using artificial intelligence

Published in Ann Rheum Dis, 2023

With the worldwide digitalisation of medical records, electronic health records (EHRs) have become an increasingly important source of real-world data (RWD). RWD can complement traditional study designs because it captures almost the complete variety of patients, leading to more generalisable results. For rheumatology, these data are particularly interesting as our diseases are uncommon and often take years to develop. In this review, we discuss the following concepts related to the use of EHR for research and considerations for translation into clinical care: EHR data contain a broad collection of healthcare data covering the multitude of real-life patients and the healthcare processes related to their care. Machine learning (ML) is a powerful method that allows us to leverage a large amount of heterogeneous clinical data for clinical algorithms, but requires extensive training, testing, and validation. Patterns discovered in EHR data using ML are applicable to real life settings, however, are also prone to capturing the local EHR structure and limiting generalisability outside the EHR(s) from which they were developed. Population studies on EHR necessitates knowledge on the factors influencing the data available in the EHR to circumvent biases, for example, access to medical care, insurance status. In summary, EHR data represent a rapidly growing and key resource for real-world studies. However, transforming RWD EHR data for research and for real-world evidence using ML requires knowledge of the EHR system and their differences from existing observational data to ensure that studies incorporate rigorous methods that acknowledge or address factors such as access to care, noise in the data, missingness and indication bias.

Recommended citation: Knevel R, Liao KP. (2023) "From real-world electronic health record data to real-world results using artificial intelligence" Ann Rheum Dis. 2023 Mar;82(3):306-311. doi: 10.1136/ard-2022-222626. Epub 2022 Sep 23.
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The Role of Genetics in Clinically Suspect Arthralgia and Rheumatoid Arthritis Development: A Large Cross-Sectional Study

Published in Arthritis Rheumatol, 2023

To investigate whether established genetic predictors for rheumatoid arthritis (RA) differentiate healthy controls, patients with clinically suspect arthralgia (CSA), and RA patients.

Recommended citation: Maurits MP, Wouters F, Niemantsverdriet E, Huizinga TWJ, van den Akker EB, Le Cessie S, van der Helm-van Mil AHM, Knevel R. (2023) "The Role of Genetics in Clinically Suspect Arthralgia and Rheumatoid Arthritis Development: A Large Cross-Sectional Study" Arthritis Rheumatol. 2023 Feb;75(2):178-186. doi: 10.1002/art.42323. Epub 2022 Dec 13.
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Author Correction: Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits

Published in Nat Commun, 2023

Liu L(1), Khan A(1), Sanchez-Rodriguez E(1), Zanoni F(1), Li Y(1), Steers N(1), Balderes O(1), Zhang J(1), Krithivasan P(1), LeDesma RA(2), Fischman C(3), Hebbring SJ(4), Harley JB(5)(6)(7), Moncrieffe H(5)(6), Kottyan LC(5)(6), Namjou-Khales B(5)(6), Walunas TL(8), Knevel R(9), Raychaudhuri S(9), Karlson EW(9), Denny JC(10), Stanaway IB(11), Crosslin D(12), Rauen T(13), Floege J(13), Eitner F(13)(14), Moldoveanu Z(15), Reily C(15), Knoppova B(15), Hall S(15), Sheff JT(15), Julian BA(15), Wyatt RJ(16), Suzuki H(17), Xie J(18), Chen N(18), Zhou X(19), Zhang H(19), Hammarström L(20), Viktorin A(21), Magnusson PKE(21), Shang N(22), Hripcsak G(22), Weng C(22), Rundek T(23)(24), Elkind MSV(25), Oelsner EC(1), Barr RG(26)(27), Ionita-Laza I(28), Novak J(15), Gharavi AG(1), Kiryluk K(29).

Recommended citation: Liu L, Khan A, Sanchez-Rodriguez E, Zanoni F, Li Y, Steers N, Balderes O, Zhang J, Krithivasan P, LeDesma RA, Fischman C, Hebbring SJ, Harley JB, Moncrieffe H, Kottyan LC, Namjou-Khales B, Walunas TL, Knevel R, Raychaudhuri S, Karlson EW, Denny JC, Stanaway IB, Crosslin D, Rauen T, Floege J, Eitner F, Moldoveanu Z, Reily C, Knoppova B, Hall S, Sheff JT, Julian BA, Wyatt RJ, Suzuki H, Xie J, Chen N, Zhou X, Zhang H, Hammarström L, Viktorin A, Magnusson PKE, Shang N, Hripcsak G, Weng C, Rundek T, Elkind MSV, Oelsner EC, Barr RG, Ionita-Laza I, Novak J, Gharavi AG, Kiryluk K. (2023) "Author Correction: Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits" Nat Commun. 2023 Feb 6;14(1):655. doi: 10.1038/s41467-023-36340-3.
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Recommendation to implementation of remote patient monitoring in rheumatology: lessons learned and barriers to take

Published in RMD Open, 2023

Remote patient monitoring (RPM) leverages advanced technology to monitor and manage patients’ health remotely and continuously. In 2022 European Alliance of Associations for Rheumatology (EULAR) points-to-consider for remote care were published to foster adoption of RPM, providing guidelines on where to position RPM in our practices. Sample papers and studies describe the value of RPM. But for many rheumatologists, the unanswered question remains the ‘how to?’ implement RPM.Using the successful, though not frictionless example of the Southmead rheumatology department, we address three types of barriers for the implementation of RPM: service, clinician and patients, with subsequent learning points that could be helpful for new teams planning to implement RPM. These address, but are not limited to, data governance, selecting high quality cost-effective solutions and ensuring compliance with data protection regulations. In addition, we describe five lacunas that could further improve RPM when addressed: establishing quality standards, creating a comprehensive database of available RPM tools, integrating data with electronic patient records, addressing reimbursement uncertainties and improving digital literacy among patients and healthcare professionals.

Recommended citation: Hamann P, Knitza J, Kuhn S, Knevel R. (2023) "Recommendation to implementation of remote patient monitoring in rheumatology: lessons learned and barriers to take" RMD Open. 2023 Dec 6;9(4):e003363. doi: 10.1136/rmdopen-2023-003363.
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The Application of Genetic Risk Scores in Rheumatic Diseases: A Perspective

Published in Genes (Basel), 2023

Modest effect sizes have limited the clinical applicability of genetic associations with rheumatic diseases. Genetic risk scores (GRSs) have emerged as a promising solution to translate genetics into useful tools. In this review, we provide an overview of the recent literature on GRSs in rheumatic diseases. We describe six categories for which GRSs are used: (a) disease (outcome) prediction, (b) genetic commonalities between diseases, (c) disease differentiation, (d) interplay between genetics and environmental factors, (e) heritability and transferability, and (f) detecting causal relationships between traits. In our review of the literature, we identified current lacunas and opportunities for future work. First, the shortage of non-European genetic data restricts the application of many GRSs to European populations. Next, many GRSs are tested in settings enriched for cases that limit the transferability to real life. If intended for clinical application, GRSs are ideally tested in the relevant setting. Finally, there is much to elucidate regarding the co-occurrence of clinical traits to identify shared causal paths and elucidate relationships between the diseases. GRSs are useful instruments for this. Overall, the ever-continuing research on GRSs gives a hopeful outlook into the future of GRSs and indicates significant progress in their potential applications.

Recommended citation: Vaskimo LM, Gomon G, Naamane N, Cordell HJ, Pratt A, Knevel R. (2023) "The Application of Genetic Risk Scores in Rheumatic Diseases: A Perspective" Genes (Basel). 2023 Dec 1;14(12):2167. doi: 10.3390/genes14122167.
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E-health as a sine qua non for modern healthcare

Published in RMD Open, 2022

In each era we need to balance between being able to provide care with our "technical skill, scientific knowledge, and human understanding" (Harrison’s Principles of Internal Medicine, 1950) to the individual patient and simultaneously ensure that our healthcare serves all. With the increasing demand of healthcare by an aging population and the lack of specialists, accessible healthcare within a reasonable time frame is not always guaranteed. E-health provides solutions for current situations where we do not meet our own aims of good healthcare, such as restrictions in access to care and a reduction in care availability by a reducing workforce. In addition, telemedicine offers opportunities to improve our healthcare beyond what is possible by in person visits. However, e-health is often viewed as an deficient version of healthcare of low quality. We disagree with this view. In this article we will discuss how to position e-health in the current situation of healthcare, given the continuing rapid development of digital technologies and the changing needs of healthcare professionals and patients. We will address the evolution of e-health towards connected and intelligent systems and the stakeholders perspective, aiming to open up the discussion on e-Health.

Recommended citation: Knevel R, Hügle T. (2022) "E-health as a sine qua non for modern healthcare" RMD Open. 2022 Sep;8(2):e002401. doi: 10.1136/rmdopen-2022-002401.
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Anti-citrullinated protein antibodies dominate the association of long-term outcomes and anti-modified protein antibodies in rheumatoid arthritis

Published in Lancet Rheumatol, 2022

DOI: 10.1016/S2665-9913(22)00095-9PMID: 38294031

Recommended citation: van Wesemael TJ, Verstappen M, Knevel R, van der Helm-van Mil AHM, Toes REM, van der Woude D. (2022) "Anti-citrullinated protein antibodies dominate the association of long-term outcomes and anti-modified protein antibodies in rheumatoid arthritis" Lancet Rheumatol. 2022 May;4(5):e316-e317. doi: 10.1016/S2665-9913(22)00095-9.
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Development and validation of an early warning model for hospitalized COVID-19 patients: a multi-center retrospective cohort study

Published in Intensive Care Med Exp, 2022

Timely identification of deteriorating COVID-19 patients is needed to guide changes in clinical management and admission to intensive care units (ICUs). There is significant concern that widely used Early warning scores (EWSs) underestimate illness severity in COVID-19 patients and therefore, we developed an early warning model specifically for COVID-19 patients.

Recommended citation: Smit JM, Krijthe JH, Tintu AN, Endeman H, Ludikhuize J, van Genderen ME, Hassan S, El Moussaoui R, Westerweel PE, Goekoop RJ, Waverijn G, Verheijen T, den Hollander JG, de Boer MGJ, Gommers DAMPJ, van der Vlies R, Schellings M, Carels RA, van Nieuwkoop C, Arbous SM, van Bommel J, Knevel R, de Rijke YB, Reinders MJT. (2022) "Development and validation of an early warning model for hospitalized COVID-19 patients: a multi-center retrospective cohort study" Intensive Care Med Exp. 2022 Sep 19;10(1):38. doi: 10.1186/s40635-022-00465-4.
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The Disconnect Between Development and Intended Use of Clinical Prediction Models for Covid-19: A Systematic Review and Real-World Data Illustration

Published in Front Epidemiol, 2022

The SARS-CoV-2 pandemic has boosted the appearance of clinical predictions models in medical literature. Many of these models aim to provide guidance for decision making on treatment initiation. Special consideration on how to account for post-baseline treatments is needed when developing such models. We examined how post-baseline treatment was handled in published Covid-19 clinical prediction models and we illustrated how much estimated risks may differ according to how treatment is handled.

Recommended citation: Prosepe I, Groenwold RHH, Knevel R, Pajouheshnia R, van Geloven N. (2022) "The Disconnect Between Development and Intended Use of Clinical Prediction Models for Covid-19: A Systematic Review and Real-World Data Illustration" Front Epidemiol. 2022 Jun 27;2:899589. doi: 10.3389/fepid.2022.899589. eCollection 2022.
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Determining in which pre-arthritis stage HLA-shared epitope alleles and smoking exert their effect on the development of rheumatoid arthritis

Published in Ann Rheum Dis, 2022

The human leukocyte antigen-shared epitope (HLA-SE) alleles and smoking are the most prominent genetic and environmental risk factors for rheumatoid arthritis (RA). However, at which pre-arthritis stage (asymptomatic/symptomatic) they exert their effect is unknown. We aimed to determine whether HLA-SE and smoking are involved in the onset of autoantibody positivity, symptoms (clinically suspect arthralgia (CSA)) and/or progression to clinical arthritis.

Recommended citation: Wouters F, Maurits MP, van Boheemen L, Verstappen M, Mankia K, Matthijssen XME, Dorjée AL, Emery P, Knevel R, van Schaardenburg D, Toes REM, van der Helm-van Mil AHM. (2022) "Determining in which pre-arthritis stage HLA-shared epitope alleles and smoking exert their effect on the development of rheumatoid arthritis" Ann Rheum Dis. 2022 Jan;81(1):48-55. doi: 10.1136/annrheumdis-2021-220546. Epub 2021 Jul 20.
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Rheumatic?-A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study

Published in Front Med (Lausanne), 2022

Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a risk score for several rheumatic diseases. We ran a pilot study retrospectively testing Rheumatic? for its ability to differentiate symptoms from existing or emerging immune-mediated rheumatic diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics.MATERIALS AND

Recommended citation: Knevel R, Knitza J, Hensvold A, Circiumaru A, Bruce T, Evans S, Maarseveen T, Maurits M, Beaart-van de Voorde L, Simon D, Kleyer A, Johannesson M, Schett G, Huizinga T, Svanteson S, Lindfors A, Klareskog L, Catrina A. (2022) "Rheumatic?-A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study" Front Med (Lausanne). 2022 Apr 25;9:774945. doi: 10.3389/fmed.2022.774945. eCollection 2022.
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HLA-B*08 Identified as the Most Prominently Associated Major Histocompatibility Complex Locus for Anti-Carbamylated Protein Antibody-Positive/Anti-Cyclic Citrullinated Peptide-Negative Rheumatoid Arthritis

Published in Arthritis Rheumatol, 2021

Previously, only the HLA-DRB1 alleles have been assessed in rheumatoid arthritis (RA). The aim of the present study was to identify the key major histocompatibility complex (MHC) susceptibility factors showing a significant association with anti-carbamylated protein antibody-positive (anti-CarP+) RA.

Recommended citation: Regueiro C, Casares-Marfil D, Lundberg K, Knevel R, Acosta-Herrera M, Rodriguez-Rodriguez L, Lopez-Mejias R, Perez-Pampin E, Triguero-Martinez A, Nuño L, Ferraz-Amaro I, Rodriguez-Carrio J, Lopez-Pedrera R, Robustillo-Villarino M, Castañeda S, Remuzgo-Martinez S, Alperi M, Alegre-Sancho JJ, Balsa A, Gonzalez-Alvaro I, Mera A, Fernandez-Gutierrez B, Gonzalez-Gay MA, Trouw LA, Grönwall C, Padyukov L, Martin J, Gonzalez A. (2021) "HLA-B*08 Identified as the Most Prominently Associated Major Histocompatibility Complex Locus for Anti-Carbamylated Protein Antibody-Positive/Anti-Cyclic Citrullinated Peptide-Negative Rheumatoid Arthritis" Arthritis Rheumatol. 2021 Jun;73(6):963-969. doi: 10.1002/art.41630. Epub 2021 Apr 23.
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New risk model is able to identify patients with a low risk of progression in systemic sclerosis

Published in RMD Open, 2021

To develop a prediction model to guide annual assessment of systemic sclerosis (SSc) patients tailored in accordance to disease activity.

Recommended citation: van Leeuwen NM, Maurits M, Liem S, Ciaffi J, Ajmone Marsan N, Ninaber M, Allaart C, Gillet van Dongen H, Goekoop R, Huizinga T, Knevel R, De Vries-Bouwstra J. (2021) "New risk model is able to identify patients with a low risk of progression in systemic sclerosis" RMD Open. 2021 May;7(2):e001524. doi: 10.1136/rmdopen-2020-001524.
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Disease progression in systemic sclerosis

Published in Rheumatology (Oxford), 2021

DOI: 10.1093/rheumatology/keaa911PMCID: PMC7937017PMID: 33404661 [Indexed for MEDLINE]

Recommended citation: van Leeuwen NM, Liem SIE, Maurits MP, Ninaber M, Marsan NA, Allaart CF, Huizinga TWJ, Knevel R, de Vries-Bouwstra JK. (2021) "Disease progression in systemic sclerosis" Rheumatology (Oxford). 2021 Mar 2;60(3):1565-1567. doi: 10.1093/rheumatology/keaa911.
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Handwork vs machine: a comparison of rheumatoid arthritis patient populations as identified from EHR free-text by diagnosis extraction through machine-learning or traditional criteria-based chart review

Published in Arthritis Res Ther, 2021

Electronic health records (EHRs) offer a wealth of observational data. Machine-learning (ML) methods are efficient at data extraction, capable of processing the information-rich free-text physician notes in EHRs. The clinical diagnosis contained therein represents physician expert opinion and is more consistently recorded than classification criteria components.OBJECTIVES: To investigate the overlap and differences between rheumatoid arthritis patients as identified either from EHR free-text through the extraction of the rheumatologist diagnosis using machine-learning (ML) or through manual chart-review applying the 1987 and 2010 RA classification criteria.

Recommended citation: Maarseveen TD, Maurits MP, Niemantsverdriet E, van der Helm-van Mil AHM, Huizinga TWJ, Knevel R. (2021) "Handwork vs machine: a comparison of rheumatoid arthritis patient populations as identified from EHR free-text by diagnosis extraction through machine-learning or traditional criteria-based chart review" Arthritis Res Ther. 2021 Jun 22;23(1):174. doi: 10.1186/s13075-021-02553-4.
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Interactions Between Genome-Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus

Published in Arthritis Rheumatol, 2020

To identify interactions between genetic factors and current or recent smoking in relation to risk of developing systemic lupus erythematosus (SLE).

Recommended citation: Cui J, Raychaudhuri S, Karlson EW, Speyer C, Malspeis S, Guan H, Sparks JA, Ni H, Liu X, Stevens E, Williams JN, Davenport EE, Knevel R, Costenbader KH. (2020) "Interactions Between Genome-Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus" Arthritis Rheumatol. 2020 Nov;72(11):1863-1871. doi: 10.1002/art.41414. Epub 2020 Sep 23.
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Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis

Published in Immunol Rev, 2020

Rheumatoid arthritis (RA) risk has a large genetic component (~60%) that is still not fully understood. This has hampered the design of effective treatments that could promise lifelong remission. RA is a polygenic disease with 106 known genome-wide significant associated loci and thousands of small effect causal variants. Our current understanding of RA risk has suggested cell-type-specific contexts for causal variants, implicating CD4 + effector memory T cells, as well as monocytes, B cells and stromal fibroblasts. While these cellular states and categories are still mechanistically broad, future studies may identify causal cell subpopulations. These efforts are propelled by advances in single cell profiling. Identification of causal cell subpopulations may accelerate therapeutic intervention to achieve lifelong remission.

Recommended citation: Amariuta T, Luo Y, Knevel R, Okada Y, Raychaudhuri S. (2020) "Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis" Immunol Rev. 2020 Mar;294(1):188-204. doi: 10.1111/imr.12827. Epub 2019 Nov 28.
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Machine Learning Electronic Health Record Identification of Patients with Rheumatoid Arthritis: Algorithm Pipeline Development and Validation Study

Published in JMIR Med Inform, 2020

Financial codes are often used to extract diagnoses from electronic health records. This approach is prone to false positives. Alternatively, queries are constructed, but these are highly center and language specific. A tantalizing alternative is the automatic identification of patients by employing machine learning on format-free text entries.OBJECTIVE: The aim of this study was to develop an easily implementable workflow that builds a machine learning algorithm capable of accurately identifying patients with rheumatoid arthritis from format-free text fields in electronic health records.

Recommended citation: Maarseveen TD, Meinderink T, Reinders MJT, Knitza J, Huizinga TWJ, Kleyer A, Simon D, van den Akker EB, Knevel R. (2020) "Machine Learning Electronic Health Record Identification of Patients with Rheumatoid Arthritis: Algorithm Pipeline Development and Validation Study" JMIR Med Inform. 2020 Nov 30;8(11):e23930. doi: 10.2196/23930.
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Toward Earlier Diagnosis Using Combined eHealth Tools in Rheumatology: The Joint Pain Assessment Scoring Tool (JPAST) Project

Published in JMIR Mhealth Uhealth, 2020

Outcomes of patients with inflammatory rheumatic diseases have significantly improved over the last three decades, mainly due to therapeutic innovations, more timely treatment, and a recognition of the need to monitor response to treatment and to titrate treatments accordingly. Diagnostic delay remains a major challenge for all stakeholders. The combination of electronic health (eHealth) and serologic and genetic markers holds great promise to improve the current management of patients with inflammatory rheumatic diseases by speeding up access to appropriate care. The Joint Pain Assessment Scoring Tool (JPAST) project, funded by the European Union (EU) European Institute of Innovation and Technology (EIT) Health program, is a unique European project aiming to enable and accelerate personalized precision medicine for early treatment in rheumatology, ultimately also enabling prevention. The aim of the project is to facilitate these goals while at the same time, reducing cost for society and patients.

Recommended citation: Knitza J, Knevel R, Raza K, Bruce T, Eimer E, Gehring I, Mathsson-Alm L, Poorafshar M, Hueber AJ, Schett G, Johannesson M, Catrina A, Klareskog L; JPAST Group. (2020) "Toward Earlier Diagnosis Using Combined eHealth Tools in Rheumatology: The Joint Pain Assessment Scoring Tool (JPAST) Project" JMIR Mhealth Uhealth. 2020 May 15;8(5):e17507. doi: 10.2196/17507.
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The eMERGE genotype set of 83,717 subjects imputed to ~40 million variants genome wide and association with the herpes zoster medical record phenotype

Published in Genet Epidemiol, 2019

The Electronic Medical Records and Genomics (eMERGE) network is a network of medical centers with electronic medical records linked to existing biorepository samples for genomic discovery and genomic medicine research. The network sought to unify the genetic results from 78 Illumina and Affymetrix genotype array batches from 12 contributing medical centers for joint association analysis of 83,717 human participants. In this report, we describe the imputation of eMERGE results and methods to create the unified imputed merged set of genome-wide variant genotype data. We imputed the data using the Michigan Imputation Server, which provides a missing single-nucleotide variant genotype imputation service using the minimac3 imputation algorithm with the Haplotype Reference Consortium genotype reference set. We describe the quality control and filtering steps used in the generation of this data set and suggest generalizable quality thresholds for imputation and phenotype association studies. To test the merged imputed genotype set, we replicated a previously reported chromosome 6 HLA-B herpes zoster (shingles) association and discovered a novel zoster-associated loci in an epigenetic binding site near the terminus of chromosome 3 (3p29).

Recommended citation: Stanaway IB, Hall TO, Rosenthal EA, Palmer M, Naranbhai V, Knevel R, Namjou-Khales B, Carroll RJ, Kiryluk K, Gordon AS, Linder J, Howell KM, Mapes BM, Lin FTJ, Joo YY, Hayes MG, Gharavi AG, Pendergrass SA, Ritchie MD, de Andrade M, Croteau-Chonka DC, Raychaudhuri S, Weiss ST, Lebo M, Amr SS, Carrell D, Larson EB, Chute CG, Rasmussen-Torvik LJ, Roy-Puckelwartz MJ, Sleiman P, Hakonarson H, Li R, Karlson EW, Peterson JF, Kullo IJ, Chisholm R, Denny JC, Jarvik GP; eMERGE Network; Crosslin DR. (2019) "The eMERGE genotype set of 83,717 subjects imputed to ~40 million variants genome wide and association with the herpes zoster medical record phenotype" Genet Epidemiol. 2019 Feb;43(1):63-81. doi: 10.1002/gepi.22167. Epub 2018 Oct 8.
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Genetic associations with radiological damage in rheumatoid arthritis: Meta-analysis of seven genome-wide association studies of 2,775 cases

Published in PLoS One, 2019

Previous studies of radiological damage in rheumatoid arthritis (RA) have used candidate-gene approaches, or evaluated single genome-wide association studies (GWAS). We undertook the first meta-analysis of GWAS of RA radiological damage to: (1) identify novel genetic loci for this trait; and (2) test previously validated variants.

Recommended citation: Traylor M, Knevel R, Cui J, Taylor J, Harm-Jan W, Conaghan PG, Cope AP, Curtis C, Emery P, Newhouse S, Patel H, Steer S, Gregersen P, Shadick NA, Weinblatt ME, Van Der Helm-van Mil A, Barrett JH, Morgan AW, Lewis CM, Scott IC. (2019) "Genetic associations with radiological damage in rheumatoid arthritis: Meta-analysis of seven genome-wide association studies of 2,775 cases" PLoS One. 2019 Oct 9;14(10):e0223246. doi: 10.1371/journal.pone.0223246. eCollection 2019.
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