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Janahiraman S, Shahril NS, Jayaraj VJ, Ch'ng S, Eow LH, Mageswaren E, Lim AL, Chong HC, Ong PS, Ismail AM, Rahim SMA, Ng CR, Suahilai DM, Ramlan AH, Too CL, Leong CO. A hierarchical cluster analysis for clinical profiling of tofacitinib treatment response in patients with rheumatoid arthritis. Clin Rheumatol 2024; 43:2489-2501. [PMID: 38922551 DOI: 10.1007/s10067-024-07035-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 05/19/2024] [Accepted: 06/14/2024] [Indexed: 06/27/2024]
Abstract
Tofacitinib is the first oral JAK inhibitor approved for treating rheumatoid arthritis (RA). To enhance our understanding of tofacitinib drug response, we used hierarchical clustering to analyse the profiles of patient who responded to the treatment in a real-world setting. Patients who commenced on tofacitinib treatment were selected from 12 major rheumatology centres in Malaysia. The aim was to assess their response to tofacitinib defined as achieving DAS28-CRP/ESR ≤ 3.2 and DAS28 improvement > 1.2 at 12 weeks. A hierarchical clustering analysis was performed using sociodemographic and clinical parameters at baseline. All 163 RA patients were divided into three clusters (Clusters 1, 2 and 3) based on specific clinical factors at baseline including bone erosion, antibody positivity, disease activity and anaemia status. Cluster 1 consisted of RA patients without bone erosion, antibody negative, low baseline disease activity measure and absence of anaemia. Cluster 2 comprised of patients without bone erosion, RF positivity, anti-CCP negativity, moderate to high baseline disease activity score and absence of anaemia. Cluster 3 patients had bone erosion, antibody positivity, high baseline disease activity and anaemia. The response rates to tofacitinib varied among the clusters: Cluster 1 had a 79% response rate, Cluster 2 had a 66% response rate, and Cluster 3 had a 36% response rate. The differences in response rates between the three clusters were found to be statistically significant. This cluster analysis study indicates that patients who are seronegative and have low disease activity, absence of bone erosion and no signs of anaemia may have a higher likelihood of benefiting from tofacitinib therapy. By identifying clinical profiles that respond to tofacitinib treatment, we can improve treatment stratification yielding significant benefits and better health outcomes for individuals with RA.
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Affiliation(s)
- Sivakami Janahiraman
- School of Postgraduate Studies, IMU University, Kuala Lumpur, Malaysia.
- Department of Pharmacy, Hospital Selayang, Ministry of Health Malaysia, Selangor Darul Ehsan, Malaysia.
| | - Nor Shuhaila Shahril
- Rheumatology Unit, Department of Medicine, Hospital Putrajaya, Ministry of Health Malaysia, Putrajaya, Malaysia
| | - Vivek Jason Jayaraj
- Sector for Biostatistics & Data Repository, National Institutes of Health Complex, Ministry of Health Malaysia, Selangor Darul Ehsan, Malaysia
| | - Suyin Ch'ng
- Rheumatology Unit, Department of Medicine, Hospital Selayang, Ministry of Health Malaysia, Selangor Darul Ehsan, Malaysia
| | - Liu Hong Eow
- Rheumatology Unit, Department of Medicine, Hospital Tuanku Ja'afar Seremban, Ministry of Health Malaysia, Negeri Sembilan, Malaysia
| | - Eashwary Mageswaren
- Rheumatology Unit, Department of Medicine, Hospital Tengku Ampuan Rahimah, Ministry of Health Malaysia, Selangor Darul Ehsan, Malaysia
| | - Ai Lee Lim
- Rheumatology Unit, Department of Medicine, Hospital Pulau Pinang, Ministry of Health Malaysia, Pulau Pinang, Malaysia
| | - Hwee Cheng Chong
- Rheumatology Unit, Department of Medicine, Hospital Melaka, Ministry of Health Malaysia, Melaka, Malaysia
| | - Ping Seung Ong
- Rheumatology Unit, Department of Medicine, Hospital Raja Permaisuri Bainun, Ministry of Health Malaysia, Perak Darul Ridzuan, Malaysia
| | - Asmahan Mohamed Ismail
- Rheumatology Unit, Department of Medicine, Hospital Raja Perempuan Zainab II, Ministry of Health Malaysia, Kelantan Darul Naim, Malaysia
| | - Siti Mariam Ab Rahim
- Rheumatology Unit, Department of Medicine, Hospital Sultanah Nur Zahirah, Ministry of Health Malaysia, Terengganu Darul Iman, Malaysia
| | - Chun Ruh Ng
- Rheumatology Unit, Department of Medicine, Hospital Sultan Ismail, Ministry of Health Malaysia, Johor Darul Ta'zim, Malaysia
| | - Dayang Masyrinartie Suahilai
- Rheumatology Unit, Department of Medicine, Hospital Tengku Ampuan Afzan, Ministry of Health Malaysia, Pahang Darul Makmur, Malaysia
| | - Azwarina Hanim Ramlan
- Rheumatology Unit, Department of Medicine, Hospital Sultanah Bahiyah, Ministry of Health Malaysia, Kedah Darul Aman, Malaysia
| | - Chun Lai Too
- Immunogenetic Unit, Institute for Medical Research, National Institutes of Health Complex, Ministry of Health Malaysia, Selangor Darul Ehsan, Malaysia
| | - Chee Onn Leong
- Centre for Cancer and Stem Cell Research Development and Innovation (IRDI), Institute for Research, IMU University, Kuala Lumpur, Malaysia
- AGTC Genomics, Kuala Lumpur, Malaysia
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Mariette F, Le Guern V, Nguyen Y, Yelnik C, Morel N, Hachulla E, Lambert M, Guettrot-Imbert G, Mouthon L, Ebbo M, Costedoat-Chalumeau N. Cluster analysis of clinical manifestations assigns systemic lupus erythematosus-phenotype subgroups: A multicentre study on 440 patients. Joint Bone Spine 2024; 91:105760. [PMID: 38972539 DOI: 10.1016/j.jbspin.2024.105760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 06/10/2024] [Accepted: 06/14/2024] [Indexed: 07/09/2024]
Abstract
OBJECTIVE Systemic lupus erythematous (SLE) is a heterogenous disease characterised by a large panel of autoantibodies and a wide spectrum of clinical signs and symptoms that engender different outcomes. We aimed to identify distinct, homogeneous SLE patients' phenotypes. METHODS This retrospective study enrolled SLE patients meeting the Systemic Lupus International Collaborating Clinics (SLICC) classification criteria, enrolled in the French multicentre "APS (antiphospholipid syndrome) and SLE" Registry. Based on 29 variables selected to cover a broad range of clinical and laboratory (excluding autoantibodies) SLE manifestations, unsupervised multiple correspondence analysis followed by hierarchical ascendent-clustering analysis assigned different phenotypes. RESULTS We included 440 patients, mostly women (94.3%). Median age at SLE diagnosis was 24 (IQR 19-32) years. Cluster analysis yielded three distinct subgroups based on cumulative clinical manifestations, not autoantibody pattern. Cluster 1 (n=91) comprised mostly Caucasian patients, with APS-associated clinical and biological manifestations, e.g., livedo, seizure, thrombocytopaenia and haemolytic anaemia. Cluster 2 (n=221), the largest, included patients with mild clinical manifestations, mainly articular, more frequently associated with Sjögren's syndrome and with less frequent autoantibody-positivity. Cluster 3 (n=128) consisted of patients with the largest panel of SLE-specific clinical manifestations (cutaneous, articular, proliferative nephritis, pleural, cardiac and haematological), the most frequent autoantibody-positivity, low complement levels, and more often of Asian and sub-Saharan African origin. CONCLUSION This unsupervised clustering method distinguished three distinct SLE patient subgroups, highlighting SLE heterogeneity.
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Affiliation(s)
- Fanny Mariette
- Department of Internal Medicine, Aix-Marseille université, hôpital La Timone, AP-HM, Marseille, France.
| | - Véronique Le Guern
- National Referral Centre for Rare Autoimmune and Systemic Diseases, Department of Internal Medicine, université de Paris, hôpital Cochin, AP-HP Centre, Paris, France
| | - Yann Nguyen
- National Referral Centre for Rare Autoimmune and Systemic Diseases, Department of Internal Medicine, université de Paris, hôpital Cochin, AP-HP Centre, Paris, France; Unité Inserm 1153, centre de recherche en épidémiologie et statistiques (CRESS), université de Paris, Paris, France
| | - Cécile Yelnik
- Inserm, Department of Internal Medicine and Clinical Immunology, U1286 - INFINITE - Institute for Translational Research in Inflammation, Referral Centre for rare systemic autoimmune diseases North and North-West of France (CeRAINO), CHU de Lille, université de Lille, Lille, France
| | - Nathalie Morel
- National Referral Centre for Rare Autoimmune and Systemic Diseases, Department of Internal Medicine, université de Paris, hôpital Cochin, AP-HP Centre, Paris, France
| | - Eric Hachulla
- Unité Inserm 1153, centre de recherche en épidémiologie et statistiques (CRESS), université de Paris, Paris, France; Inserm, Department of Internal Medicine and Clinical Immunology, U1286 - INFINITE - Institute for Translational Research in Inflammation, Referral Centre for rare systemic autoimmune diseases North and North-West of France (CeRAINO), CHU de Lille, université de Lille, Lille, France
| | - Marc Lambert
- Inserm, Department of Internal Medicine and Clinical Immunology, U1286 - INFINITE - Institute for Translational Research in Inflammation, Referral Centre for rare systemic autoimmune diseases North and North-West of France (CeRAINO), CHU de Lille, université de Lille, Lille, France
| | - Gaëlle Guettrot-Imbert
- National Referral Centre for Rare Autoimmune and Systemic Diseases, Department of Internal Medicine, université de Paris, hôpital Cochin, AP-HP Centre, Paris, France
| | - Luc Mouthon
- National Referral Centre for Rare Autoimmune and Systemic Diseases, Department of Internal Medicine, université de Paris, hôpital Cochin, AP-HP Centre, Paris, France
| | - Mikael Ebbo
- Department of Internal Medicine, Aix-Marseille université, hôpital La Timone, AP-HM, Marseille, France
| | - Nathalie Costedoat-Chalumeau
- National Referral Centre for Rare Autoimmune and Systemic Diseases, Department of Internal Medicine, université de Paris, hôpital Cochin, AP-HP Centre, Paris, France; Unité Inserm 1153, centre de recherche en épidémiologie et statistiques (CRESS), université de Paris, Paris, France
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Collacott H, Phillips-Beyer A, Krucien N, Flamion B, Marsh K. Patients' Preferences for Systemic Lupus Erythematosus Treatments-A Discrete Choice Experiment. THE PATIENT 2024; 17:287-300. [PMID: 38270788 DOI: 10.1007/s40271-023-00670-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/17/2023] [Indexed: 01/26/2024]
Abstract
BACKGROUND Symptoms of systemic lupus erythematosus (SLE) vary between patients, but those of increased disease activity typically include musculoskeletal and mucocutaneous manifestations such as joint pain, swelling, and rashes. Several treatment options are available to patients with SLE with variable efficacy. Many treatments, especially corticosteroids, cause unwanted side effects, although little is currently known about patients' preferences for treatments of SLE. OBJECTIVE We aimed to identify which attributes of SLE treatment are valued by patients and to quantify their relative importance. METHODS Adult participants with moderate-to-severe SLE were asked to make a series of choices between two hypothetical treatments in an online discrete choice experiment (DCE). A latent class model (LCL) was estimated to analyze choice data. Relative attribute importance (RAI) was calculated to determine the importance of each attribute to participants. RESULTS A total of 342 participants from the USA completed the survey. A three-class LCL model was found to have the best fit. Class 1 (non-attenders) had non-significant preferences across all attributes. To achieve a better fit, a constrained LCL (cLCL) model was run with the two remaining classes. The most important attributes for participants in class 2 (benefit-seekers) were joint pain (RAI = 32.0%), non-joint pain (RAI = 21.8%), fatigue (RAI = 20.1%), and skin rashes and itching (RAI = 19.1%). The most important attributes for participants in class 3 (risk-avoiders) were risk of non-severe side effects from corticosteroids (RAI = 28.4%), risk of severe side effects from corticosteroids (RAI = 21.4%), and the risk of infections (RAI = 19.2%). Risk-avoiders were more likely to have been diagnosed with SLE for a longer period (>1 year) and were more likely to have experience with oral corticosteroids. CONCLUSIONS SLE patients fall into two groups with distinct preferences: benefit-seekers, who prioritize reducing the impact of disease symptoms, and risk-avoiders, who prioritize avoiding treatment risks. The implication of this finding will depend on the reasons for these differences, which warrant further research. Our study suggests that these differences arise due to the impact of disease and treatment experience on preferences. If so, well-informed patients may not be willing to tolerate the risks associated with oral corticosteroids in exchange for their benefits.
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Choi MY, Chen I, Clarke AE, Fritzler MJ, Buhler KA, Urowitz M, Hanly J, St-Pierre Y, Gordon C, Bae SC, Romero-Diaz J, Sanchez-Guerrero J, Bernatsky S, Wallace DJ, Isenberg DA, Rahman A, Merrill JT, Fortin PR, Gladman DD, Bruce IN, Petri M, Ginzler EM, Dooley MA, Ramsey-Goldman R, Manzi S, Jönsen A, Alarcón GS, van Vollenhoven RF, Aranow C, Mackay M, Ruiz-Irastorza G, Lim S, Inanc M, Kalunian K, Jacobsen S, Peschken C, Kamen DL, Askanase A, Buyon JP, Sontag D, Costenbader KH. Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes. Ann Rheum Dis 2023; 82:927-936. [PMID: 37085289 DOI: 10.1136/ard-2022-223808] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 04/06/2023] [Indexed: 04/23/2023]
Abstract
OBJECTIVES A novel longitudinal clustering technique was applied to comprehensive autoantibody data from a large, well-characterised, multinational inception systemic lupus erythematosus (SLE) cohort to determine profiles predictive of clinical outcomes. METHODS Demographic, clinical and serological data from 805 patients with SLE obtained within 15 months of diagnosis and at 3-year and 5-year follow-up were included. For each visit, sera were assessed for 29 antinuclear antibodies (ANA) immunofluorescence patterns and 20 autoantibodies. K-means clustering on principal component analysis-transformed longitudinal autoantibody profiles identified discrete phenotypic clusters. One-way analysis of variance compared cluster enrolment demographics and clinical outcomes at 10-year follow-up. Cox proportional hazards model estimated the HR for survival adjusting for age of disease onset. RESULTS Cluster 1 (n=137, high frequency of anti-Smith, anti-U1RNP, AC-5 (large nuclear speckled pattern) and high ANA titres) had the highest cumulative disease activity and immunosuppressants/biologics use at year 10. Cluster 2 (n=376, low anti-double stranded DNA (dsDNA) and ANA titres) had the lowest disease activity, frequency of lupus nephritis and immunosuppressants/biologics use. Cluster 3 (n=80, highest frequency of all five antiphospholipid antibodies) had the highest frequency of seizures and hypocomplementaemia. Cluster 4 (n=212) also had high disease activity and was characterised by multiple autoantibody reactivity including to antihistone, anti-dsDNA, antiribosomal P, anti-Sjögren syndrome antigen A or Ro60, anti-Sjögren syndrome antigen B or La, anti-Ro52/Tripartite Motif Protein 21, antiproliferating cell nuclear antigen and anticentromere B). Clusters 1 (adjusted HR 2.60 (95% CI 1.12 to 6.05), p=0.03) and 3 (adjusted HR 2.87 (95% CI 1.22 to 6.74), p=0.02) had lower survival compared with cluster 2. CONCLUSION Four discrete SLE patient longitudinal autoantibody clusters were predictive of long-term disease activity, organ involvement, treatment requirements and mortality risk.
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Affiliation(s)
- May Yee Choi
- Medicine, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada
| | - Irene Chen
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Ann Elaine Clarke
- Medicine, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada
| | - Marvin J Fritzler
- Medicine, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada
| | - Katherine A Buhler
- Medicine, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada
| | - Murray Urowitz
- Center for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital, University of Toronto, Lupus Clinic, Toronto, Ontario, Canada
| | - John Hanly
- Division of Rheumatology, Department of Medicine and Department of Pathology, Queen Elizabeth II Health Sciences Centre and Dalhousie University, Halifax, Nova Scotia, Canada
| | - Yvan St-Pierre
- Medicine, Research Institute of the McGill University Health Center, Montreal, Quebec, Canada
| | - Caroline Gordon
- Rheumatology Research Group, Institute of Inflammation and Ageing, College of Medical and Dental Sciences, Birmingham University Medical School, Birmingham, West Midlands, UK
| | - Sang-Cheol Bae
- Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Hanyang University Institute for Rheumatology and Hanyang University Institute of Bioscience and Biotechnology, Seoul, The Republic of Korea
| | - Juanita Romero-Diaz
- Immunology and Rheumatology, Instituto Nacional de Ciencias Médicas y Nutrición, Mexico City, Mexico
| | - Jorge Sanchez-Guerrero
- Mount Sinai Hospital and University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Sasha Bernatsky
- Divisions of Rheumatology and Clinical Epidemiology, McGill University Health Centre, Montreal, Quebec, Canada
| | - Daniel J Wallace
- Division of Rheumatology, Cedars-Sinai/David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - David Alan Isenberg
- Centre for Rheumatology, Department of Medicine, University College London, London, UK
| | - Anisur Rahman
- Centre for Rheumatology, Department of Medicine, University College London, London, UK
| | - Joan T Merrill
- Department of Clinical Pharmacology, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Paul R Fortin
- Division of Rheumatology, CHU de Québec - Université Laval, Quebec City, Quebec, Canada
| | - Dafna D Gladman
- Center for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital, University of Toronto, Lupus Clinic, Toronto, Ontario, Canada
| | - Ian N Bruce
- Epidemiology Unit, University of Manchester, Manchester, UK
| | - Michelle Petri
- Division of Rheumatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Ellen M Ginzler
- Department of Medicine, SUNY Downstate Medical Center, Brooklyn, New York, USA
| | - Mary Anne Dooley
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Rosalind Ramsey-Goldman
- Department of Medicine, Division of Rheumatology, Northwestern University and Feinberg School of Medicine, Chicago, Illinois, USA
| | - Susan Manzi
- Medicine, Allegheny Health Network, Pittsburgh, Pennsylvania, USA
| | | | - Graciela S Alarcón
- Department of Medicine, The University of Alabama at Birmingham Heersink School of Medicine, Birmingham, Alabama, USA
| | | | - Cynthia Aranow
- Division of Autoimmune and Musculoskeletal Disease, Feinstein Institute for Medical Research, Manhasset, New York, USA
| | - Meggan Mackay
- Division of Autoimmune and Musculoskeletal Disease, Feinstein Institute for Medical Research, Manhasset, New York, USA
| | - Guillermo Ruiz-Irastorza
- Autoimmune Diseases Research Unit, Department of Internal Medicine, BioCruces Health Research Institute, Hospital Universitario Cruces, University of the Basque Country, Barakaldo, Spain
| | - Sam Lim
- Division of Rheumatology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Murat Inanc
- Department of Internal Medicine, Division of Rheumatology, Istanbul University, Istanbul Medical Faculty, Istanbul, Turkey
| | - Kenneth Kalunian
- Department of Rheumatology, Allergy and Immunology, University of California San Diego, La Jolla, California, USA
| | - Søren Jacobsen
- Department of Rheumatology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | | | - Diane L Kamen
- Division of Rheumatology & Immunology, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Anca Askanase
- Hospital for Joint Diseases, New York University, Seligman Centre for Advanced Therapeutics, New York, New York, USA
| | - Jill P Buyon
- Division of Rheumatology, New York University School of Medicine, New York, New York, USA
| | - David Sontag
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Karen H Costenbader
- Department of Medicine, Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Medicine, Harvard Medical School, Boston, Massachusetts, USA
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Complement as a Biomarker for Systemic Lupus Erythematosus. Biomolecules 2023; 13:biom13020367. [PMID: 36830735 PMCID: PMC9953581 DOI: 10.3390/biom13020367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 02/06/2023] [Accepted: 02/10/2023] [Indexed: 02/17/2023] Open
Abstract
Systemic lupus erythematosus (SLE) is a disease of immune complex deposition; therefore, complement plays a vital role in the pathogenesis of SLE. In general, complement levels in blood and complement deposition in histological tests are used for the management of SLE. Thus, the evaluation of complement status can be useful in the diagnosis of SLE, assessment of disease activity, and prediction of treatment response and prognosis. In addition, novel complement biomarkers, such as split products and cell-bound complement activation products, are considered to be more sensitive than traditional complement markers, such as serum C3 and C4 levels and total complement activity (CH50), which become more widely used. In this review, we report the complement testing in the management of SLE over the last decade and summarize their utility.
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Sjöwall C, Parodis I. Clinical Heterogeneity, Unmet Needs and Long-Term Outcomes in Patients with Systemic Lupus Erythematosus. J Clin Med 2022; 11:jcm11226869. [PMID: 36431345 PMCID: PMC9695498 DOI: 10.3390/jcm11226869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 11/17/2022] [Indexed: 11/23/2022] Open
Abstract
The clinical presentation of systemic lupus erythematosus (SLE) is highly heterogeneous, ranging from mild disease limited to skin and joint involvement to life-threatening conditions with renal impairment, severe cytopenias, central nervous system disease, and thromboembolic events [...].
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Affiliation(s)
- Christopher Sjöwall
- Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection/Rheumatology, Linköping University, SE-581 85 Linköping, Sweden
- Correspondence: ; Tel.: +46-10-1032416
| | - Ioannis Parodis
- Department of Medicine Solna, Division of Rheumatology, Karolinska Institutet and Karolinska University Hospital, SE-171 76 Stockholm, Sweden
- Department of Rheumatology, Faculty of Medicine and Health, Örebro University, SE-701 82 Örebro, Sweden
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