Abstracts tagged "Statistical methods"

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: 0106 • ACR Convergence 2020
A Machine Learning-derived Radiomics Nomogram for Diagnosis of Osteoporosis and Osteopenia
Qianrong Xie¹, Yue Chen², Yimei Hu³, Fanwei Zeng⁴, Pingxi Wang⁴, Lin Xu⁵, Jianhong Wu⁶, Jie Li¹, Jing Zhu⁷, Ming Xiang⁸ and Fanxin Zeng⁹, ¹Department of Clinical Research Center, Dazhou Central Hospital, Dazhou, China (People's Republic), ²Department of Clinical Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China (People's Republic), ³Department of Orthopedics, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China (People's Republic), ⁴Department of bone disease, Dazhou Central Hospital, Dazhou, China (People's Republic), ⁵Department of medical imaging, Dazhou Central Hospital, Dazhou, China (People's Republic), ⁶Department of Rheumatology, Dazhou Central Hospital, Dazhou, China (People's Republic), ⁷Department of Rheumatology and Immunology, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Chengdu, China (People's Republic), ⁸Department of Orthopedics, Sichuan Provincial Orthopedic Hospital, Chengdu, China (People's Republic), ⁹Department of Clinical Research Center, Dazhou Central Hospital, Dazhou, Sichuan, China (People's Republic)
Background/Purpose: To discriminate osteoporosis and osteopenia using a quantitative computed tomography (QCT) radiomics signatures and clinical variables.Methods: This retrospective study enrolled 635 patients with QCT images and clinical characteristics from November…
Abstract Number: 0487 • ACR Convergence 2020
Association Between an Extended Lifestyle Score and Adverse Health-related Outcomes in People with Rheumatoid Arthritis: A Study of 5295 UK Biobank Participants
Jordan Canning¹, Stefan Siebert², Bhautesh Jani¹, Frances Mair¹ and Barbara Nicholl¹, ¹University of Glasgow, Glasgow, Scotland, United Kingdom, ²University of Glasgow, Glasgow, United Kingdom
Background/Purpose: Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterised by inflammation of the synovial joints. Traditional lifestyle factors, such as smoking and poor diet,…
Abstract Number: 0613 • ACR Convergence 2020
Modeling the Effects of Covid-19 Protective Behaviors and Healthcare Delivery on the Health of Patients with Rheumatic Disease
Kevin Kennedy¹, Emily Sirotich², Salman Surangiwala³, Maggie Larche², Mitchell Levine¹ and Jonathan Hausmann⁴, ¹McMaster University, Hamilton, Canada, ²McMaster University, Hamilton, ON, Canada, ³Queen’s School of Medicine, Kingston, Canada, ⁴Boston Children's Hospital / Beth Israel Deaconess Medical Center, Cambridge, MA
Background/Purpose: COVID-19 has caused global disruptions in the management of chronic illnesses. The extent to which patients with rheumatic disease have been affected by COVID-19…
Abstract Number: 1009 • ACR Convergence 2020
Missing Data and Multiple Imputation in Rheumatoid Arthritis Registries Using Sequential Random Forest Method
Ahmed Al-Saber¹, Adeeba Al-Herz², Jiazhu Pan¹, Khulood Saleh³, Adel Al-Awadhi⁴, Waleed Al-Kandari³, Eman Hasan⁵, Aqeel Ghanem⁶, Mohammed Hussain⁵, Yaser Ali⁷, Ebrahim Nahar⁷, Ahmad Alenizi⁸, Sawsan Hayat⁷, Fatemah Abutiban⁹, Ali Aldei⁵, Amjad Alkadi¹⁰, Heba Alhajeri⁷, Husain Behbehani³, Naser Alhadhood³, Khaled Mokaddem⁵, Ahmed Khadrawy³, Ammad Fazal³, Agaz Zaman⁷, Ghada Mazloum⁷, Youssef Bartella⁵, Sally Hamed⁵ and Ramia Alsouk⁸, ¹Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom, ²Al-Amiri Hospital, Kuwait City, Kuwait, ³Farwania Hosiptal, Farwania, Kuwait, ⁴Faculty of Medicine, Kuwait University, Jabria, Kuwait, ⁵Al-Amiri Hospital, Kuwait, Kuwait, ⁶Mubarak Al-Kabeer Hospital, Kuwait City, Kuwait, ⁷Mubarak Al-Kabeer Hospital, Hawally, Kuwait, ⁸Jahra Hospital, Jahra, Kuwait, ⁹Rheumatology Unit, Department of Medicine, Jaber Alahmed Alsabah hospital, State of Kuwait, Jahra, Kuwait, ¹⁰Sabah Hospital, Kuwait, Kuwait
Background/Purpose: Missing data in clinical epidemiological researches violate the intention to treat principle, reduce statistical power and can induce bias if they are related to…
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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