Abstracts tagged "Statistical methods"

Abstract Number: 1470 • ACR Convergence 2020
Machine Learning-Based Prediction of Knee Replacement in Persons with and Without Radiographic Osteoarthritis Using Clinical and Imaging Features of Osteoarthritis: The Multicenter Osteoarthritis Study
S. Reza Jafarzadeh¹, David Felson¹, Michael Nevitt², James Torner³, Cora Lewis⁴, Frank Roemer⁵, Ali Guermazi¹ and Tuhina Neogi¹, ¹Boston University School of Medicine, Boston, MA, ²University of California, San Francisco, San Francisco, CA, ³University of Iowa, Iowa City, IA, ⁴University of Alabama Birmingham, Birmingham, AL, ⁵Boston University School of Medicine, Boston, MA, and Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany, Erlangen, Germany
Background/Purpose: Prior studies of predictors of knee replacement (KR) have often included only a limited set of risk factors, been conducted primarily in knees with…
Abstract Number: 1487 • ACR Convergence 2020
Biclustering Reveals Potential Knee Osteoarthritis Phenotypes in Exploratory Analyses: Data from the Osteoarthritis Initiative
Amanda Nelson¹, Thomas Keefe², Todd Schwartz³, Richard Loeser¹, Yvonne Golightly⁴, Liubov Arbeeva¹ and J Marron², ¹University of North Carolina at Chapel Hill Thurston Arthritis Research Center, Chapel Hill, NC, ²University of North Carolina at Chapel Hill, Chapel Hill, NC, ³University of North Carolina at Chapel Hill Dept of Biostatistics, Chapel Hill, NC, ⁴University of North Carolina at Chapel Hill Dept of Epidemiology, Chapel Hill, NC
Background/Purpose: To utilize novel methodologies to explore subgroups within the OAI clinical data.Methods: From the OAI baseline dataset (n=4796 individuals with or at risk of…
Abstract Number: 1734 • ACR Convergence 2020
The Challenge of Assessing Wellbeing from the Patients` Perspective in Early Rheumatoid Arthritis
Diederik De Cock¹, Tianna Poffe², Geert Verbeke², Sofia Pazmino¹, Veerle Stouten¹, Delphine Bertrand¹, Rene Westhovens³ and Patrick Verschueren⁴, ¹KU Leuven, Leuven, Belgium, ²KU Leuven, Leuven, ³University Hospitals Leuven, Belgium, Leuven, Belgium, ⁴University Hospital Leuven, Leuven, Belgium
Background/Purpose: Although more effective therapeutics and treatment strategies for Rheumatoid Arthritis (RA) have improved many patient-reported outcomes (PROs), still a sizeable number of patients in…
Abstract Number: 1745 • ACR Convergence 2020
A Novel Method for Predicting 1-Year Retention of Abatacept Using Machine Learning Techniques
Rieke Alten¹, Claire Behar², Christine Boileau², Pierre Merckaert², Ebenezer Afari², Virginie Vannier-Moreau³, Sean Connolly³, Yedid Elbez², Pierre-Antoine Juge⁴ and Karissa Lozenski³, ¹Schlosspark-Klinik, Universitätsmedizin, Berlin, Germany, ²Excelya, Boulogne-Billancourt, France, ³Bristol-Myers Squibb Company, Princeton, NJ, ⁴Université de Paris, Service de Rhumatologie Hôpital Bichat-Claude Bernard, AP-HP, Paris, France
Background/Purpose: In the ACTION (NCT02109666) study, using multivariable Cox proportional hazards regression models, patient (pt) global assessment of pain, country, reason for stopping last biologic,…
Abstract Number: 1763 • ACR Convergence 2020
Blending Hierarchical Cluster Analysis and Cluster-Specific Regressions to Predict Clinical Outcome to Tofacitinib Treatment in Patients with Rheumatoid Arthritis
Robert Landewé¹, Daniel H Solomon², Gianluca Bonfanti³, Luigi Manca³, John C Woolcott⁴, Jasper Deuring⁵, Stephen Watt⁶, Pritha Bhadra Brown⁶, Rebecca Germino⁶, Birol Emir⁶ and Roger A Edwards⁷, ¹Amsterdam University Medical Center & Zuyderland Hospital, Amsterdam, Netherlands, ²Brigham and Women's Hospital, Boston, MA, ³Fair Dynamics Consulting, SRL, Milan, Italy, ⁴Pfizer Inc, Collegeville, PA, ⁵Pfizer Inc, Rotterdam, Netherlands, ⁶Pfizer Inc, New York, NY, ⁷Health Services Consulting Corporation, Boxborough, MA
Background/Purpose: Patients with RA exhibit wide variations in response to therapy. Early treatment response profiles may help us to better predict subsequent treatment response, thus…
Abstract Number: 1957 • ACR Convergence 2020
A Single Cell Stromal Atlas Identifies Conserved Fibroblast Phenotypes Expanded in the Inflamed Synovium, Lung, Intestine, and Salivary Gland
Ilya Korsunsky¹, Kevin Wei², Mathilde Pohin³, Edy Kim⁴, Jason Turner⁵, Saba Nayar⁶, Benjamin Fisher⁷, Karim Raza⁸, Matthias Friedrich⁹, Jennifer Marshall⁵, Adam Croft⁵, Mark Coles¹⁰, Andreas Frei¹¹, Andrew Filer¹², Francesca Barone⁵, Kara Lassen¹¹, Fiona Powrie¹⁰, Christopher Buckley¹³, Michael Brenner² and Soumya Raychaudhuri¹⁴, ¹Brigham and Women's Hospital, Boston, MA, ²Brigham and Women's Hospital and Harvard Medical School, Boston, MA, ³Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, Oxford, United Kingdom, ⁴Brigham and Women’s Hospital, Division of Pulmonary and Critical Care Medicine, Boston, MA, ⁵Rheumatology Research Group, Institute for Inflammation and Ageing, College of Medical and Dental Sciences, University of Birmingham, Queen Elizabeth Hospital, Birmingham, United Kingdom, ⁶Institute for Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom, ⁷University Hospitals Birmingham NHS Foundation Trust-Birmingham, Birmingham, United Kingdom, ⁸Sandwell and West Birmingham Hospitals NHS Trust, Birmingham, United Kingdom, ⁹Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science, University of Oxford, Oxford, United Kingdom, ¹⁰Kennedy Institute of Rheumatology, University of Oxford, Oxford, United Kingdom, ¹¹Roche Pharma Research and Early Development, Immunology, Infectious Diseases and Ophthalmology (I2O) Discovery and Translational Area, Roche Innovation Center Basel, Basel, Switzerland, ¹²Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom, ¹³University of Birmingham, Birmingham, United Kingdom, ¹⁴Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
Background/Purpose: Pro-inflammatory fibroblasts have been independently implicated in the pathogenesis of rheumatoid arthritis (RA), inflammatory bowel disease (IBD), interstitial lung disease (ILD), and Sjogren’s syndrome…
Abstract Number: 2412 • 2019 ACR/ARP Annual Meeting
Use of Minimal Important Difference (MID) in Randomized Clinical Trials of Pain in Osteoarthritis
Lavalley Michael¹, Matthew Parkes ², Daniel White ³, Stephan Reichebach ⁴, Timothy McAlindon ⁵ and David Felson ⁶, ¹Boston University, Boston, ²University of Manchester, Manchester, England, United Kingdom, ³University of Delaware, Newark, DE, ⁴University of Bern, Bern, Switzerland, ⁵Tufts Medical Center, Boston, MA, ⁶Boston University School of Medicine, Department of Rheumatology, Boston
Background/Purpose: Minimal important differences (MID), based on within-subject evaluation of attaining an improvement in a continuous outcome such as a pain scale, are important for…
Abstract Number: 2535 • 2019 ACR/ARP Annual Meeting
Identifying Subgroups of SLE Patients with Differential Responses to a BLyS Inhibitor: Application of a Machine Learning Algorithm to Clinical Trial Data
Mimi Kim¹, Kith Pradhan ¹, Peter Izmirly ², Kenneth Kalunian ³, Leslie Hanrahan ⁴ and Joan Merrill ⁵, ¹Albert Einstein College of Medicine, Bronx, NY, ²New York University School of Medicine, New York, ³University of California at San Diego, San Diego, ⁴Lupus Foundation of America, Washington DC, ⁵Oklahoma Medical Research Foundation, Oklahoma City
Background/Purpose: Given the heterogeneity of systemic lupus erythematosus (SLE), the effect of any intervention is expected to vary. The ability to identify those most and…
Abstract Number: 1157 • 2018 ACR/ARHP Annual Meeting
Acknowledged Biostatistical Help and the Quality of Statistical Analyses in Randomized Controlled Trials in Rheumatology
Elif Dincses¹, Gul Guzelant², Gulen Hatemi² and Hasan Yazici³, ¹Istanbul University, Cerrahpasa Medical Faculty, Department of Internal Medicine, Division of Rheumatology, İstanbul, Turkey, ²Istanbul University, Cerrahpasa Medical Faculty, Department of Internal Medicine, Division of Rheumatology, Istanbul, Turkey, ³Istanbul Academic Hospital, Istanbul, Turkey
Background/Purpose: The quality of statistical analysis reporting is wanting even in our most prestigious journals. It stands to reason that active participation of biostatisticians/epidemiologists (b/e)…
Abstract Number: 2051 • 2017 ACR/ARHP Annual Meeting
The Lasso Selection Model in Rheumatology Epidemiologic Studies
Sofia Pedro¹, Bella Mehta², Gulsen Ozen^3,4 and Kaleb Michaud^1,5, ¹National Data Bank for Rheumatic Diseases, Wichita, KS, ²Rheumatology, Hospital of Special Surgery, New York, NY, ³Rheumatology, Marmara University, School of Medicine, Rheumatology, Istanbul, Turkey, ⁴Department of Rheumatology, University of Nebraska Medical Center, Omaha, NE, ⁵University of Nebraska Medical Center, Omaha, NE
Background/Purpose: Selecting the best model in an epidemiologic analysis is challenging as it addresses problems like confounding and allows the estimation of unbiased results. Stepwise…

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