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: 0123 • ACR Convergence 2023
Improving Interpretation of Work Outcomes in Patients with Inflammatory Rheumatic Musculoskeletal Disease: General Population Reference Curves for Work Ability and At-work Productivity
Dafne Capelusnik¹, Wouter Smeets², Casper Webers³, Sofia Ramiro⁴, Elena Nikiphorou⁵, Roel Braekers², Laura Boekel⁶, Gertjan Wolbink⁷ and Annelies Boonen⁸, ¹Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, ²Data science institute, Hasselt University, Hasselt, Belgium, ³Maastricht University, Maastricht, Netherlands, ⁴Department of Rheumatology, Leiden University Medical Center, Leiden, Netherlands, ⁵King's College London, London, United Kingdom, ⁶Amsterdam Rheumatology and Immunology Center, Location Reade, Department of Rheumatology, Amsterdam, Netherlands, ⁷Reade, Amsterdam, Netherlands, ⁸Care and Public Health Research Institute (Caphri), Maastricht University, Maastricht, Netherlands
Background/Purpose: Data on self-reported presenteeism (limitations or reduced work productivity at work) in persons with inflammatory rheumatic and musculoskeletal diseases (iRMD) are challenging to interpret…
Abstract Number: 0175 • ACR Convergence 2023
Predicting Cost-Related Medication Non-Adherence in US Adults with Chronic Arthritis: A Machine Learning Approach
Ashkan Ara¹, Matthew Chenoweth¹ and Christopher Scannell², ¹University of California Los Angeles, Los Angeles, CA, ²UCLA / West Los Angeles VA Medical Center, Los Angeles, CA
Background/Purpose: Cost-related medication non-adherence (CRN) occurs when patients are unable to follow their prescribed medication regimen due to financial constraints, such as high costs or…
Abstract Number: 0512 • ACR Convergence 2023
Factors Associated with Treatment Pathways in Early Axial Spondyloarthritis: A Multistate Analysis of the 10-year Follow-up of the DESIR Cohort
Elodie Portier¹, Sylvie chevret², Adeline Ruyssen-Witrand³, Anouk Walter-Petrich², Maxime Dougados⁴ and Anna Molto⁵, ¹Hôpital Cochin, Paris, France, ²Saint Louis Hospital, Paris, France, ³Toulouse University Hospital, Toulouse, France, ⁴Rheumatology Department, Cochin Hospital; INSERM (U1153): Clinical Epidemiology and Biostatistics, University of Paris, Paris, France, ⁵HOPITAL COCHIN AP-HP, Service de Rhumatologie, Paris, France
Background/Purpose: Current recommendations for the management of patients with axial spondyloarthritis (axSpA) emphasize the need of individualized strategy in the therapeutic decision. Thus, many factors…
Abstract Number: 0613 • ACR Convergence 2023
Quantification of Skin Hardness of Patients with Systemic Sclerosis Using SOFTGRAM
Hiraku Kokubu¹, Yasuaki Ikuno¹, Kazuyuki Uchiyama¹, Miwa Kato¹, Mayuka Yamamoto¹, Haruki Asada¹, Satona Rikitake¹, Yoshimichi Kobayashi¹, Takahiro Koike¹, Syuji Sugiura¹, Takuma Hayami¹, Kensuke Yoneta¹, Toshifumi Takahashi¹, Bunpei Yamamoto¹, Takeshi Kato¹, Yoshito Kunisaki², Makoto Nakatani², Kohei Okamoto² and Noriki Fujimoto¹, ¹Shiga University of Medical Science, Otsu, Japan, ²ISHIDA MEDICAL CO.,LTD., Kyoto, Japan
Background/Purpose: No quantitative and objective methods for measuring skin hardness have been established. Japanese technology leads the world in the tactile sensor field, and SOFTGRAM…

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