Machine learning-driven immunophenotypic stratification of mixed connective tissue disease, corroborating the clinical heterogeneity.

Journal: Rheumatology (Oxford, England)
Published Date:

Abstract

OBJECTIVE: The objective of this study was to stratify patients with MCTD, based on their immunophenotype.

Authors

  • Shinji Izuka
    Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Toshihiko Komai
    Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Takahiro Itamiya
    Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Mineto Ota
    Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Yasuo Nagafuchi
    Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Hirofumi Shoda
    Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Kosuke Matsuki
    Research Division, Chugai Pharmaceutical Co., Ltd, Yokohama, Kanagawa, Japan.
  • Kazuhiko Yamamoto
    Osaka Electro-Communication University - Shijonawate Campus, Shijonawate, Japan.
  • Tomohisa Okamura
    Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Keishi Fujio
    Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.