Machine learning-based prediction of G-CSF-induced hematopoietic stem cell mobilization outcomes in healthy volunteers.

Journal: Bone marrow transplantation
Published Date: Jul 4, 2025

Abstract

Haematopoietic stem cell transplantation (HSC-T) has been established as a fundamental therapeutic intervention for a wide range of hematological malignancies and disorders, with a proven record of efficacy spanning over five decades. Peripheral blood (PB) has become the haematopoietic stem cell (HSC) source of choice, surpassing bone marrow, owing to its cost-effectiveness, reduced invasiveness, higher cell yields, and shorter hospitalizations. Clinically, granulocyte-colony stimulating factor (G-CSF) administration is the standard procedure for inducing HSC mobilization. Nevertheless, a significant proportion of potential donors, ranging from 5% to 10%, exhibit suboptimal mobilization responses to G-CSF. To investigate this, we carried out a retrospective analysis of mobilization data from 1056 donors who underwent G-CSF-induced HSC mobilization over the 5-year period from 2018 to 2023. This comprehensive study elucidated the complex interplay between mobilization efficacy, as measured primarily by CD34+ cell yield, and a variety of influencing factors. Our data indicate that better mobilization outcomes are achieved in male donors than female donors. Additionally, we found a positive correlation between increased body weight and improved mobilization efficiency, implying a more favourable response to G-CSF in obese donors. Moreover, the implementation of a split-dose regimen for the mobilization agent significantly improved outcomes, highlighting the critical role of dosing strategies. Notably, younger donors exhibited better mobilization responses, underscoring age as a pivotal determinant of mobilization outcomes. Leveraging machine learning (ML) algorithms, we developed seven predictive models designed to forecast G-CSF-induced HSC mobilization outcomes on the basis of these variables.

Authors

  • Ce Shi
    Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China.
  • Xiangjun Zeng
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Jimei Ge
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Yunfei Qiu
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Yi Luo
    Electrical and Computer Engineering Department, Bioengineering Department, University of California, Los Angeles, CA 90095 USA, and also with the California NanoSystems Institute, University of California, Los Angeles, CA 90095 USA.
  • Jimin Shi
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Jian Yu
    Key laboratory of Transplantation, Chinese Academy of Medical Sciences, Tianjin, 300192, China; Tianjin Key Laboratory for Organ Transplantation, Tianjin First Center Hospital, Tianjin, 300192, China; Department of Liver Transplantation, Tianjin Medical University First Center Clinical College, Tianjin, 300192, China; Tianjin Key Laboratory of Molecular and Treatment of Liver Cancer, Tianjin First Center Hospital, Tianjin, 300192, China.
  • Xiaoyu Lai
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Yamin Tan
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Lizhen Liu
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Huarui Fu
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Yishan Ye
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Luxin Yang
    Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Yibo Wu
    School of Public Health, Peking University, Beijing, China. Electronic address: bimuwuyibo@outlook.com.
  • He Huang
  • Yanmin Zhao
    Institute of Hematology, Zhejiang University, Hangzhou, China. yanminzhao@zju.edu.cn.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals