bioinformatics and rheumatoid arthritis (RA) Archives

Abstract Number: 206 • ACR/ARHP Annual Meeting 2018
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 • ACR/ARHP Annual Meeting 2017
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 • ACR/ARHP Annual Meeting 2016
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…

Abstracts tagged "bioinformatics and rheumatoid arthritis (RA)"

Impact of International Classification of Diseases 10th Revision Codes and Updated Medical Information on an Existing Rheumatoid Arthritis Phenotype Algorithm Using Electronic Medical Data

Microarray Pathway Analysis Comparing Baricitinib and Adalimumab in Moderate to Severe Rheumatoid Arthritis Patients, from a Phase 3 Study

Gene Modules Correlated with Disease Activity and Abatacept Treatment Identified with Weighted Gene Co-Expression Network Analysis of CD4+ T Cell Subsets of RA