Abstracts tagged "Statistical methods"

Abstract Number: 0479 • ACR Convergence 2024
Constructing and Using a Novel Nucleotide Transformer for Patients with Rheumatoid Arthritis
Shant Ayanian, Collin Osborne, Marc Blasi, Daniel Darveaux, Eric Klee and Elena Myasoedova, Mayo Clinic, Rochester, MN
Background/Purpose: Applying the methods of artificial intelligence (AI) to genomic data for clinical outcome prediction in rheumatoid arthritis (RA) is an area of growing research.…
Abstract Number: 0492 • ACR Convergence 2024
A Machine Learning Model for the Early Identification of Rheumatoid Arthritis: Development and Validation
Michael Dreyfuss¹, Yonatan Jenudi², Dan Riesel³, Or Ramni³, Daniel Underberger⁴, Benjamin Getz⁵, Shlomit Steinberg-Koch³, Douglas White⁶ and Elena Myasoedova⁷, ¹Predicta Med, Ramat Gan, Israel, ²[email protected], Ramat Gan, Israel, ³Predicta Med Analytics Ltd., Ramat Gan, Israel, ⁴Predicta Med Analytics Ltd., Bridgeport, CT, ⁵CTO, Ramat Gan, Israel, ⁶Gundersen Health System, Onalaska, WI, ⁷Mayo Clinic, Rochester, MN
Background/Purpose: Patients with rheumatoid arthritis often experience clinically significant delays in diagnosis (Sørensen et al., 2015; Raza et al., 2011). RA can present similarly to…
Abstract Number: 0545 • ACR Convergence 2024
Missing Data in Observational Studies: Investigating Cross-sectional Single Imputation Methods for Assessing Disease Activity in Axial Spondyloarthritis
Stylianos Georgiadis¹, Marion Pons², Simon Horskjær Rasmussen², Merete Hetland³, Louise Linde², Daniela DiGuiseppe⁴, Brigitte Michelsen⁵, Johan Karlsson Wallman⁶, Tor Olofsson⁷, Karel Pavelka⁸, Jakub Závada⁸, Bente Glintborg⁹, Anne Gitte Loft¹⁰, Catalin Codreanu¹¹, Daniel Melim¹², Diogo Esperança Almeida¹³, Tore K. Kvien¹⁴, Vappu Rantalaiho¹⁵, Ritva Peltomaa¹⁶, Bjorn Gudbjornsson¹⁷, Olafur Palsson¹⁸, Ovidiu Rotariu¹⁹, Ross MacDonald¹⁹, Ziga Rotar²⁰, Katja Perdan-Pikmajer²⁰, Karin Laas²¹, Florenzo Iannone²², Adrian Ciurea²³, Mikkel Ostergaard²⁴ and Lykke Oernbjerg¹, ¹Rigshospitalet Glostrup, Glostrup, Hovedstaden, Denmark, ²Rigshospitalet Glostrup, Glostrup, Denmark, ³Rigshospitalet Glostrup and University of Copenhagen, Glostrup, Denmark, ⁴Karolinska Institutet, Stockholm, ⁵Rigshospitalet Glostrup, Diakonhjemmet Hospital and Sørlandet Hospital, Copenhagen, Denmark, ⁶Lund University, Department of Clinical Sciences Lund, Section of Rheumatology and Skåne University Hospital, Lund, Sweden, Lund, Skane Lan, Sweden, ⁷Lund University, Department of Clinical Sciences Lund, Section of Rheumatology and Skåne University Hospital, Lund, Sweden, Lund, Sweden, ⁸Institute of Rheumatology and Charles University, Praha, Czech Republic, ⁹DANBIO, Rigshospitalet Glostrup and University of Copenhagen, Virum, Denmark, ¹⁰Aarhus University Hospital and Aarhus University, Horsens, Denmark, ¹¹University of Medicine and Pharmacy, Bucharest, Romania, ¹²Hospital Egas Moniz, Lisbon, Portugal, ¹³Hospital de Braga, Braga, Portugal, ¹⁴Center for treatment of Rheumatic and Musculoskeletal Diseases (REMEDY), Diakonhjemmet Hospital, Oslo, Norway and University of Oslo (UiO), Institute of Clinical Medicine, Oslo, Norway, Oslo, Norway, ¹⁵Tampere University Hospital, Tampere University and Kanta-Häme Central Hospital, Tampere, Finland, ¹⁶Helsinki University Hospital and University of Helsinki, Helsinki, Finland, ¹⁷Landspitali University Hospital and University of Iceland, Reykjavik, Iceland, ¹⁸University of Iceland and Skåne University Hospital, Reykjavik, Iceland, ¹⁹University of Aberdeen, Aberdeen, United Kingdom, ²⁰University Medical Centre Ljubljana and University of Ljubljana, Ljubljana, Slovenia, ²¹East-Tallinn Central Hospital, Tallinn, Estonia, ²²Rheumatology Unit- University of Bari "Aldo Moro", IT, Bari, Italy, ²³University Hospital Zurich, Zürich, Switzerland, ²⁴Department of Clinical Medicine, University of Copenhagen and Center for Rheumatology, Copenhagen Center for Arthritis Research, Glostrup, Denmark
Background/Purpose: In observational studies, several longitudinal methods have been proposed to impute missing data of an individual by using the available information of the same…
Abstract Number: 0754 • ACR Convergence 2024
Clinical Characterization of Aortitis and Periaortitis in a Cohort of 134 Patients from a Single Universitary Center. A Model-based Cluster Analysis
Carmen Secada Gómez¹, Javier Loricera², Adrián Martín-Gutiérrez³, Fernando Lopez-Gutierrez⁴, María Nuñez-Sayar⁵, Ander Ucelay-Aristi⁵, Isabel Martinez-Rodriguez⁶, ivan Ferraz-Amaro⁷, Santos Castañeda⁸ and Ricardo Blanco-Alonso⁹, ¹Rheumatology, Hospital Universitario Marqués de Valdecilla, IDIVAL, Santander, Spain, ²Hospital Universitario Marqués de Valdecilla, IDIVAL, Santander, Spain, ³Hospital Universitario Marques de Valdecilla, IDIVAL, Renedo de Piélagos, Cantabria, Spain, ⁴Rheumatology, Hospital Universitario Marqués de Valdecilla, IDIVAL, Santander, Cantabria, Spain, ⁵Cardiovascular Surgery, Hospital Universitario Marqués de Valdecilla, Santander, Cantabria, Spain, ⁶Nuclear Medicine, Hospital Universitario Marques de Valdecilla,IDIVAL, Santander, Cantabria, Spain, ⁷Rheumatology, Hospital Universitario de Canarias, Santa Cruz de Tenerife, Canarias, Spain, ⁸Hospital Universitario de la Princesa, Madrid, Spain, ⁹Division of Rheumatology, Hospital Universitario Marqués de Valdecilla. IDIVAL, Immunopathology group, Santander, Spain
Background/Purpose: Aortitis and periaortitis represent the inflammation of the aortic wall and the surrounding periaortic tissues, respectively. Both can be idiopathic or secondary to infectious…
Abstract Number: 0885 • ACR Convergence 2024
Reproducible Single Cell Annotation of Programs Underlying T-cell Subsets, Activation States, and Functions
Dylan Kotliar¹, Michelle Curtis¹, Ryan Agnew¹, Kathryn Weinand¹, Aparna Nathan², Yuriy Baglaenko¹, Yu Zhao¹, Pardis Sabeti³, Deepak Rao⁴ and Soumya Raychaudhuri¹, ¹Brigham and Women's Hospital, Boston, MA, ²Harvard Medical School, Boston, MA, ³Broad Institute, Boston, MA, ⁴Brigham and Women's Hospital, Harvard Medical School, Boston, MA

Background/Purpose: T-cells play a key role in the pathogenesis of autoimmune disease and in protection against cancer and infection. Consequently, there is widespread interest in…
Abstract Number: 1109 • ACR Convergence 2024
Differences Between Correlation and Causal Inference in Detecting Predictors of Undefined Crystal Arthropathy in Women
Laura Scagnellato¹, Antonio Collesei², Sonia farah³, Carlomaurizio Montecucco⁴, Francesca Oliviero⁵, Bernd raffeiner⁶, Marta favero⁵, Amelia Damasco⁵, doria Andrea⁵, Fausto Salaffi³ and Roberta Ramonda⁷, and SIR Study Group on Crystal Arthropaties, ¹Rheumatology Unit, University of Padova, Padova, Italy, ²IRCCS Istituto Oncologico Veneto IOV, Padova, Italy, ³Polytechnic University of Marche, Jesi (AN), Italy, ⁴IRCCS policlinico S. Matteo foundation, University of Pavia, Pavia, Italy, ⁵University of Padova, Padova, Italy, ⁶General Hospital of Bolzano, Bolzano, Italy, ⁷Rheumatology Unit, University of Padova, Italy, Padova, Italy
Background/Purpose: Crystal arthropaties, including gout and calcium pyrophosphate deposition disease (CPPD), are prevalent and burdensome conditions. The ALLSTAR model allows the identification of reliable causal,…
Abstract Number: 1191 • ACR Convergence 2024
Discordant Associations Among Chronological and Biological Age with Multi-joint Osteoarthritis and Symptom Burden: The Johnston County Health Study
Liubov Arbeeva¹, Yvonne Golightly², Cameron Kurz³, Matlock Jeffries⁴, Virginia Kraus⁵, Richard Loeser⁶, Duncan Lascelles⁷ and Amanda Nelson³, ¹University of North Carolina, Chapel Hill, Carrboro, NC, ²University of Nebraska Medical Center, Omaha, NE, ³University of North Carolina at Chapel Hill, Chapel Hill, NC, ⁴Oklahoma Medical Research Foundation, Oklahoma City, OK, ⁵Duke University, Durham, NC, ⁶University of North Carolina, Chapel Hill, NC, ⁷North Carolina State University, Raleigh, NC
Background/Purpose: Biological age (BA) may be superior to chronological age (CA) in predicting mortality and age-related conditions such as diabetes and cognitive/functional decline (PMID35715611), as…
Abstract Number: 1207 • ACR Convergence 2024
Patterns of Shared Variation in Knee Ultrasound for Osteoarthritis: A Machine Learning Approach
Sahar Sawani¹, Liubov Arbeeva², Katherine Yates³, Carolina Alvarez⁴, Todd Schwartz¹, Serena Savage-Guin⁵, Jordan Renner⁶, Catherine Bakewell⁷, Minna Kohler⁸, Janice Lin⁹, Jonathan Samuels¹⁰ and Amanda Nelson¹, ¹University of North Carolina at Chapel Hill, Chapel Hill, NC, ²University of North Carolina, Chapel Hill, Carrboro, NC, ³University of North Carolina Medical Center, Chapel Hill, NC, ⁴University of North Carolina at Chapel Hill, Miami, FL, ⁵Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill,, Chapel Hill, NC, ⁶Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, ⁷Intermountain Health Care, Salt Lake City, UT, ⁸Massachusetts General Hospital, Boston, MA, ⁹Stanford University, Palo Alto, CA, ¹⁰NYU Langone, Rye Brook, NY
Background/Purpose: The aim of this study was to utilize a machine learning (ML) approach to identify phenotypes of knee OA (KOA) based on demographic variables,…
Abstract Number: 1404 • ACR Convergence 2024
Modeling Diversity in Systemic Lupus Erythematosus (SLE) Clinical Trials Using Real-world Data (RWD) Sources
Andrew Bevan¹ and Nora Carroll², ¹Integrated Project Solutions, PPD, part of Thermo Fisher Scientific, Cambridge, United Kingdom, ²Cardiovascular and General Medicine, Thermo Fisher Scientific, Athlone, Ireland
Background/Purpose: The FDA places emphasis on studying clinically relevant trial populations but does not address how these might be defined. SLE disproportionately affects women and…
Abstract Number: 1409 • ACR Convergence 2024
Salivary Organoids Contain More Diverse Epithelial and Less Mesenchymal Cells Than Adherent Cultures: Choose Your Sjögren’s Disease Research Tool Carefully
Ting Yang¹, Abel Soto Gamez¹, Janneke Terpstra¹, Hendrika Bootsma², Arjan Vissink¹, Frans Kroese³ and Sarah Pringle³, ¹UMCG, Groningen, Netherlands, ²Department of Rheumatology and Clinical Immunology, University of Groningen, University Medical Center Groningen, Groningen, Groningen, Netherlands, ³University Medical Center Groningen, Groningen, Netherlands
Background/Purpose: The majority of the critical pieces of work probing the involvement of the salivary gland (SG) epithelium in Sjogren’s Disease (SjD) employ salivary gland…
Abstract Number: 1728 • ACR Convergence 2024
Higher Oral Steroid Dose Is Associated with Worse Survival in Immune Checkpoint Inhibitor-Treated Rheumatoid Arthritis Patients with Metastatic Non-Small Cell Lung Cancer
Deanna Jannat-Khah¹, Jeffrey Curtis², Fenglong Xie³, Ashish Saxena⁴ and Anne Bass⁵, ¹Hospital For Special Surgery, New York, NY, ²The University of Alabama at Birmingham, Birmingham, AL, ³University of Alabama at Birmingham, Birmingham, AL, ⁴Weill Cornell Medicine, New York, NY, ⁵Hospital for Special Surgery, Weill Cornell Medicine, New York, NY
Background/Purpose: It is unknown if steroid use for RA patients could interfere with the benefits of immune checkpoint inhibitors (ICI) as cancer therapies. Additionally, it…
Abstract Number: 1894 • ACR Convergence 2023
3-Dimensional Regional Variation in Inter-rater Reliability of Bone Marrow Lesion Scoring in the Knee
Stephanie Wichuk¹, Walter P. Maksymowych¹, Joel Paschke², Abhilash Hareendranathan³ and Jacob Jaremko¹, ¹University of Alberta, Edmonton, AB, Canada, ²CARE Arthritis, Edmonton, AB, Canada, ³Radiology and Diagnostic Imaging, Edmonton, AB, Canada
Background/Purpose: Bone marrow lesions (BML) are an important scoring feature on magnetic resonance imaging (MRI) of knee osteoarthritis (OA), and their presence in certain anatomical…
Abstract Number: 1901 • ACR Convergence 2023
Which ASDAS-ESR Cut-offs for Disease Activity Correspond to ASDAS-CRP Cut-offs in Axial Spondyloarthritis? – Results from the EuroSpA Collaboration
Stylianos Georgiadis¹, Lykke Ørnbjerg¹, Brigitte Michelsen², Tore Kvien³, Daniela Di Giuseppe⁴, Johan Karlsson Wallman⁵, Jakub Zavada⁶, Sella Provan⁷, Ana Maria Rodrigues⁸, Maria Jose Santos⁹, Ziga Rotar¹⁰, Dan Nordstrom¹¹, Anna-Mari Hokkanen¹², Gary Macfarlane¹³, Gareth T. Jones¹³, Irene van der Horst-Bruinsma¹⁴, Pasoon Hellamand¹⁵, Mikkel Østergaard¹⁶ and Merete Hetland¹, ¹Copenhagen Center for Arthritis Research, Rigshospitalet, Copenhagen, Denmark, ²Rigshospitalet Glostrup; Diakonhjemmet Hospital; Sørlandet Hospital, Copenhagen, Denmark, ³Center for Treatment of Rheumatic and Musculoskeletal Diseases (REMEDY), Diakonhjemmet Hospital, Oslo, Norway, ⁴Karolinska Institutet, Stockholm, Sweden, ⁵Lund University and Skåne University Hospital, Lund, Sweden, ⁶Institute of Rheumatology; Charles University, Prague, Czech Republic, ⁷Diakonhjemmet Hospital, Oslo, Norway, ⁸Sociedade Portuguesa de Reumatologia; Nova Medical School; Hospital dos Lusíadas, Lisbon, Portugal, ⁹Hospital Garcia de Orta, Almada, Lisboa, Portugal, ¹⁰University Medical Centre Ljubljana, Ljubljana, Slovenia, ¹¹Helsinki University Hospital, Helsinki, Finland, ¹²Helsinki University and Helsinki University Hospital, Helsinki, Finland, ¹³Aberdeen Centre for Arthritis and Musculoskeletal Health (Epidemiology Group), University of Aberdeen, Aberdeen, United Kingdom, ¹⁴Radboud University Medical Centre, Department of Rheumatology, Nijmegen, Netherlands, ¹⁵Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands, ¹⁶Copenhagen Center for Arthritis Research, Center for Rheumatology and Spine Diseases, Centre for Head and Orthopaedics, Rigshospitalet; University of Copenhagen, Copenhagen, Denmark
Background/Purpose: When assessing disease activity in patients with axial spondyloarthritis (axSpA), the Ankylosing Spondylitis Disease Activity Score with C-reactive protein (ASDAS-CRP) is recommended over ASDAS…
Abstract Number: 1989 • ACR Convergence 2023
Shared Variation Among Cartilage Thickness Change Maps and Baseline Clinical Features at the Initiation of Structural Knee Osteoarthritis
Thomas Keefe¹, Marc Niethammer¹, Boqi Chen¹, Zhengyang Shen¹, Daniel Nissman¹, Mary Catherine Minnig², Yvonne Golightly³, J.S. Marron¹ and Amanda Nelson¹, ¹University of North Carolina at Chapel Hill, Chapel Hill, NC, ²University of North Carolina at Chapel Hill, Durham, NC, ³University of Nebraska Medical Center, Omaha, NE
Background/Purpose: To identify features of cartilage thickness change and baseline clinical indicators associated with the transition from normal to mildly reduced joint space as an…
Abstract Number: 2213 • ACR Convergence 2023
Identification of a Diagnostic Model for Axial Spondyloarthritis in Daily Clinical Practice Using a Random Forest Machine Learning Approach
Imke Redeker¹, Styliani Tsiami², Jan Eicker³, Uta Kiltz⁴, David Kiefer², Ioana Andreica⁵, Philipp Sewerin² and Xenofon Baraliakos⁶, ¹Ruhr Universität Bochum, Bochum, Germany, ²Ruhr-Universität Bochum and Rheumazentrum Ruhrgebiet, Herne, Germany, ³Rheumazentrum Ruhrgebiet Herne and Ruhr-University Bochum, Herne, Germany, ⁴Rheumazentrum Ruhrgebiet, Herne, Germany, ⁵Rheumazentrum Ruhrgebiet Herne, Herne, Germany, ⁶Rheumazentrum Ruhrgebiet Herne, Ruhr-University Bochum, Herne, Germany
Background/Purpose: In axial spondyloarthritis (axSpA), early diagnosis plays a key role in preventing disease progression. However, a validated diagnostic algorithm does not exist, while classification…

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