Knevel Lab

Knevel Lab

Bioinformatics group of the LUMC Rheumatology department

Publications

Highlighted publications

You can also find our articles on PubMed.

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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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