An investigation of long-term outcome of rabbit anti-thymocyte globulin and cyclosporine therapy for pediatric severe aplastic anemia  

作　　者：Lixian Chang Mingchen Yan Jingliao Zhang Binghang Liu Li Zhang Ye Guo Jing Sun Yang Wan Meihui Yi Yang Lan Yuli Cai Yuanyuan Ren Haihui Zheng Aoli Zhang Zhenyu Li Jian Wang Yingrui Li Xiaofan Zhu 

机构地区：[1]State Key Laboratory of Experimental Hematology,National Clinical Research Center for Blood Diseases,Haihe Laboratory of Cell Ecosystem,Institute of Hematology&Blood Diseases Hospital,Chinese Academy of Medical Sciences&Peking Union Medical College,Tianjin,China [2]Shenzhen Digital Life Institute,Shenzhen,China

出　　处：《Blood Science》2023年第3期180-186,共7页血液科学（英文）

基　　金：supported by the CAMS Innovation Fund for Medical Sciences(CIFMS,2021-I2M-C&T-B-082);National Key Research and Development Program of China(2016YFC0901503);the National Natural Science Foundation of China(81500156,81170470).

摘　　要：Children with severe aplastic anemia(SAA)face heterogeneous prognoses after immunosuppressive therapy(IST).There are few models that can predict the long-term outcomes of IST for these patients.The objective of this paper is to develop a more effective prediction model for SAA prognosis based on clinical electronic medical records from 203 children with newly diagnosed SAA.In the early stage,a novel model for long-term outcomes of SAA patients with IST was developed using machine-learning techniques.Among the indicators related to long-term efficacy,white blood cell count,lymphocyte count,absolute reticulocyte count,lymphocyte ratio in bone-marrow smears,C-reactive protein,and the level of IL-6,IL-8 and vitamin B12 in the early stage are strongly correlated with long-term efficacy(P<.05).Taken together,we analyzed the long-term outcomes of rabbit antithymocyte globulin and cyclosporine therapy for children with SAA through machine-learning techniques,which may shorten the observation period of therapeutic effects and reduce treatment costs and time.

关 键 词：Anti-thymocyte globulin Immunosuppressive therapy Machine learning Predictive model Severe aplastic anemia 

分 类 号：R725.5[医药卫生—儿科]