Abstracts tagged "bioinformatics and rheumatoid arthritis (RA)"

Abstract Number: 206 • 2018 ACR/ARHP Annual Meeting
Impact of International Classification of Diseases 10th Revision Codes and Updated Medical Information on an Existing Rheumatoid Arthritis Phenotype Algorithm Using Electronic Medical Data
Sicong Huang¹, Jie Huang¹, Tianrun Cai², Kumar P. Dahal³, Andrew Cagan⁴, Jacklyn Stratton³, Tianxi Cai⁵ and Katherine P. Liao³, ¹Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, MA, ²Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Boston, MA, ³Brigham and Women's Hospital, Boston, MA, ⁴Research Computing, Partners HealthCare, Charlestown, MA, ⁵Harvard T.H. Chan School of Public Health, Boston, MA
Background/Purpose: Electronic medical records (EMRs) are increasingly being utilized for clinical research, where the phenotypes of interest are typically defined by algorithms. Almost a decade…
Abstract Number: 2866 • 2017 ACR/ARHP Annual Meeting
Microarray Pathway Analysis Comparing Baricitinib and Adalimumab in Moderate to Severe Rheumatoid Arthritis Patients, from a Phase 3 Study
Paul Emery¹, Peter C. Taylor², Michael Weinblatt³, Yoshiya Tanaka⁴, Edward C. Keystone⁵, Ernst R. Dow⁶, Richard Higgs⁶, William L. Macias⁶, Guilherme Rocha⁶, Terence P. Rooney⁶, Douglas E. Schlichting⁶, Steven H. Zuckerman⁶ and Iain B. McInnes⁷, ¹Leeds MSK Biomed/Chapel Allerton Hospital, Leeds, United Kingdom, ²NDORMS, University of Oxford, Oxford, United Kingdom, ³Brigham and Women’s Hospital, Boston, MA, ⁴The First Department of Internal Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan, ⁵University of Toronto, Toronto, ON, Canada, ⁶Eli Lilly and Company, Indianapolis, IN, ⁷University of Glasgow, Glasgow, United Kingdom
Background/Purpose: In RA-BEAM (NCT01710358), baricitinib (BARI), an oral selective inhibitor of Janus kinase (JAK) 1 and JAK 2, yielded significant improvements in patients (pts) with…
Abstract Number: 1565 • 2016 ACR/ARHP Annual Meeting
Gene Modules Correlated with Disease Activity and Abatacept Treatment Identified with Weighted Gene Co-Expression Network Analysis of CD4+ T Cell Subsets of RA
Shuji Sumitomo¹, Yasuo Nagafuchi¹, Yumi Tsuchida¹, Haruka Tsuchiya¹, Mineto Ota¹, Kazuyoshi ishigaki², Shinichiro Nakachi¹, Rika Kato¹, Keiichi Sakurai¹, Norio Hanata¹, Shoko Tateishi³, Hiroko Kanda³, Akari Suzuki⁴, Yuta Kochi⁴, Keishi Fujio¹ and Kazuhiko Yamamoto¹, ¹Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan, ²Laboratory for Statistical Analysis, Center for Integrative Medical Sciences, The Institute of Physical and Chemical Research (RIKEN), Yokohama, Japan, ³Department of Immunotherapy Management, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan, ⁴Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
Background/Purpose: Although there are several reports of transcriptome analysis of peripheral blood mononuclear cells (PBMC) in RA, analysis of detailed CD4+ subset and the effect…

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