Using a machine learning algorithm to predict acute graft-versus-host disease following allogeneic transplantation

Author:

Arai Yasuyuki12ORCID,Kondo Tadakazu2ORCID,Fuse Kyoko3ORCID,Shibasaki Yasuhiko3,Masuko Masayoshi3,Sugita Junichi4ORCID,Teshima Takanori4ORCID,Uchida Naoyuki5,Fukuda Takahiro6,Kakihana Kazuhiko7ORCID,Ozawa Yukiyasu8,Eto Tetsuya9,Tanaka Masatsugu10,Ikegame Kazuhiro11,Mori Takehiko12,Iwato Koji13,Ichinohe Tatsuo14,Kanda Yoshinobu15,Atsuta Yoshiko1617

Affiliation:

1. Department of Transfusion Medicine and Cell Therapy and

2. Department of Hematology and Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan;

3. Department of Hematology, Endocrinology and Metabolism, Niigata University Faculty of Medicine, Niigata, Japan;

4. Department of Hematology, Hokkaido University Hospital, Hokkaido, Japan;

5. Department of Hematology, Federation of National Public Service Personnel Mutual Aid Associations, Toranomon Hospital, Tokyo, Japan;

6. Department of Hematopoietic Stem Cell Transplantation, National Cancer Center Hospital, Tokyo, Japan;

7. Hematology Division, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan;

8. Department of Hematology, Japanese Red Cross Nagoya First Hospital, Aichi, Japan;

9. Department of Hematology, Hamanomachi Hospital, Fukuoka, Japan;

10. Department of Hematology, Kanagawa Cancer Center, Kanagawa, Japan;

11. Division of Hematology, Department of Internal Medicine, Hyogo College of Medicine, Hyogo, Japan;

12. Division of Hematology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan;

13. Department of Hematology, Hiroshima Red Cross Hospital & Atomic-bomb Survivors Hospital, Hiroshima, Japan;

14. Department of Hematology and Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan;

15. Division of Hematology, Jichi Medical University, Saitama, Japan;

16. Japanese Data Center for Hematopoietic Cell Transplantation, Nagoya, Japan; and

17. Department of Healthcare Administration, Nagoya University Graduate School of Medicine, Nagoya, Japan

Abstract

Key Points The machine learning algorithms produced clinically reasonable and robust risk stratification scores for aGVHD. Predicting scores for aGVHD also demonstrated the link between risk of development of aGVHD and overall survival after HSCT.

Publisher

American Society of Hematology

Subject

Hematology

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