Predicting apheresis yield and factors affecting peripheral blood stem cell harvesting using a machine learning model.

Journal: The Journal of international medical research
PMID: 39719078

Abstract

OBJECTIVE: Mobilization and collection of peripheral blood stem cells (PBSCs) are time-intensive and costly. Excessive apheresis sessions can cause physical discomfort for donors and increase the costs associated with collection. Therefore, it is essential to identify key predictive factors for successful harvests to minimize the need for multiple apheresis procedures.

Authors

  • Jing Qi
    China Meat Research Center, Beijing 100068, China.
  • Yinchu Chen
    Department of Hematology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, China.
  • Xiaoke Jin
    Department of Hematology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, China.
  • Ran Wang
    Department of Psychiatry, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
  • Nana Wang
    Institute of Computing Technology(ICT), Chinese Academy of Sciences(CAS), Beijing, China.
  • Jiawei Yan
    Department of Chemistry, Stanford University, Stanford, California 94305, USA.
  • Chen Huang
    Department of Pharmacy, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
  • Jun Huang
    Department of Endoscopy, Jiangxi Cancer Hospital, Nanchang, China.
  • Yuanfeng Wei
    Department of Hematology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, China.
  • Faqin Xie
    Department of Hematology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, China.
  • Zhengzhi Yu
    Department of Hematology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, China.
  • Dongping Huang
    Department of Hematology, The First Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, China.

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