1.Integrated molecular characterization of sarcomatoid hepatocellular carcinoma
Rong-Qi SUN ; Yu-Hang YE ; Ye XU ; Bo WANG ; Si-Yuan PAN ; Ning LI ; Long CHEN ; Jing-Yue PAN ; Zhi-Qiang HU ; Jia FAN ; Zheng-Jun ZHOU ; Jian ZHOU ; Cheng-Li SONG ; Shao-Lai ZHOU
Clinical and Molecular Hepatology 2025;31(2):426-444
Background:
s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated.
Methods:
In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs.
Results:
Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment.
Conclusions
We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.
2.Integrated molecular characterization of sarcomatoid hepatocellular carcinoma
Rong-Qi SUN ; Yu-Hang YE ; Ye XU ; Bo WANG ; Si-Yuan PAN ; Ning LI ; Long CHEN ; Jing-Yue PAN ; Zhi-Qiang HU ; Jia FAN ; Zheng-Jun ZHOU ; Jian ZHOU ; Cheng-Li SONG ; Shao-Lai ZHOU
Clinical and Molecular Hepatology 2025;31(2):426-444
Background:
s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated.
Methods:
In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs.
Results:
Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment.
Conclusions
We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.
3.Integrated molecular characterization of sarcomatoid hepatocellular carcinoma
Rong-Qi SUN ; Yu-Hang YE ; Ye XU ; Bo WANG ; Si-Yuan PAN ; Ning LI ; Long CHEN ; Jing-Yue PAN ; Zhi-Qiang HU ; Jia FAN ; Zheng-Jun ZHOU ; Jian ZHOU ; Cheng-Li SONG ; Shao-Lai ZHOU
Clinical and Molecular Hepatology 2025;31(2):426-444
Background:
s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated.
Methods:
In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs.
Results:
Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment.
Conclusions
We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.
4.Estimation of genotoxicity threshold induced by acute exposure to neodymium nitrate in mice using benchmark dose
Junli LIU ; Yu DING ; Xueqing CHENG ; Zhengli YANG ; Kelei QIAN ; Jing XU ; Yiyun FAN ; Dongsheng YU ; Zhiqing ZHENG ; Jun YANG ; Ning WANG ; Xinyu HONG
Journal of Environmental and Occupational Medicine 2024;41(4):425-430
Background The benchmark dose (BMD) method calculates the dose associated with a specific change in response based on a specific dose-response relationship. Compared with the traditional no observed adverse effect level (NOAEL) method, the BMD method has many advantages, and the 95% lower confidence limit of benchmark dose lower limit (BMDL) is recommended to replace NOAEL in deriving biological exposure limits. No authority has yet published any health-based guideline for rare earth elements. Objective To evaluate genotoxicity threshold induced by acute exposure to neodymium nitrate in mice using BMD modeling through micronucleus test and comet assay. Methods SPF grade mice (n=90) were randomly divided into nine groups, including seven neodymium nitrate exposure groups, one control group (distilled water), and one positive control group (200 mg·kg−1 ethyl methanesulfonate), 10 mice in each group, half male and half female. The seven dose groups were fed by gavage with different concentrations of neodymium nitrate solution (male: 14, 27, 39, 55, 77, 109, and 219 mg·kg−1; female: 24, 49, 69, 97, 138, 195, and 389 mg·kg−1) twice at an interval of 21 h. Three hours after the last exposure, the animals were neutralized by cervical dislocation. The bone marrow of mice femur was taken to calculate the micronucleus rate of bone marrow cells, and the liver and stomach were taken for comet test. Results The best fitting models for the increase of polychromatophil micronucleus rate in bone marrow of female and male mice induced by neodymium nitrate were the exponential 4 model and the hill model, respectively. The BMD and the BMDL of female mice were calculated to be 31.37 mg·kg−1 and 21.90 mg·kg−1, and those of male mice were calculated to be 58.62 mg·kg−1 and 54.31 mg·kg−1, respectively. The best fitting models for DNA damage induced by neodymium nitrate in female and male mouse hepatocytes were the exponential 5 model and the exponential 4 model, respectively, and the calculated BMD and BMDL were 27.15 mg·kg−1 and 11.99 mg·kg−1 for female mice, and 16.28 mg·kg−1 and 10.47 mg·kg−1 for male mice, respectively. The hill model was the best fitting model for DNA damage of gastric adenocytes in both female and male mice, and the calculated BMD and BMDL were 36.73 mg·kg−1 and 19.92 mg·kg−1 for female mice, and 24.74 mg·kg−1 and 14.08 mg·kg−1 for male mice, respectively. Conclusion Taken the micronucleus rate of bone marrow cells, DNA damage of liver cells and gastric gland cells as the end points of genotoxicity, the BMDL of neodymium nitrate is 10.47 mg·kg−1, which can be used as the threshold of genotoxic effects induced by acute exposure to neodymium nitrate in mice.
5.Experts consensus on standard items of the cohort construction and quality control of temporomandibular joint diseases (2024)
Min HU ; Chi YANG ; Huawei LIU ; Haixia LU ; Chen YAO ; Qiufei XIE ; Yongjin CHEN ; Kaiyuan FU ; Bing FANG ; Songsong ZHU ; Qing ZHOU ; Zhiye CHEN ; Yaomin ZHU ; Qingbin ZHANG ; Ying YAN ; Xing LONG ; Zhiyong LI ; Yehua GAN ; Shibin YU ; Yuxing BAI ; Yi ZHANG ; Yanyi WANG ; Jie LEI ; Yong CHENG ; Changkui LIU ; Ye CAO ; Dongmei HE ; Ning WEN ; Shanyong ZHANG ; Minjie CHEN ; Guoliang JIAO ; Xinhua LIU ; Hua JIANG ; Yang HE ; Pei SHEN ; Haitao HUANG ; Yongfeng LI ; Jisi ZHENG ; Jing GUO ; Lisheng ZHAO ; Laiqing XU
Chinese Journal of Stomatology 2024;59(10):977-987
Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.
6.Study on the construction of evaluation index system for multisectoral cooperation in chronic disease prevention and control under the strategy of Healthy China
Yu-Mei HUANG ; Li-Zheng GUAN ; Li-Guang SUN ; You-Li HAN ; Ning ZHANG ; Yan-Bing ZENG ; Cheng-Yu MA
Chinese Journal of Health Policy 2024;17(6):10-16
Objective:In order to construct a multisectoral cooperation evaluation index system for chronic disease prevention and control in the Healthy China strategy,so as to provide a reference for the evaluation and improvement of multisectoral cooperation work.Methods:The initial indicator system was constructed based on D'Amour's cooperative structure model.Fifteen public health experts were selected to refine the evaluation indicators through two rounds of expert consultation using the Delphi method.Then weights of indicators were assigned according to AHP.Results:Experts'positive coefficient,level of authority and coordination of opinions were confirmed.The finalized evaluation index system for multisectoral cooperation in chronic disease prevention and control contains 5 first-level indicators,12 second-level indicators and 34 third-level indicators.According to the weight,the indicators in first level were Shared Goals and Vision(0.222 8),Internalization(0.158 7),Formalization(0.252 3),Governance(0.154 5)and Cooperation effects(0.211 8).Conclusions:The evaluation index system applicable to multisectoral cooperation in the prevention and control of chronic diseases in counties(cities/districts)is preliminarily established,which is highly scientific and operable,and lays the foundation for the next step of application and promotion.
7.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
8.Development and validation of a stromal-immune signature to predict prognosis in intrahepatic cholangiocarcinoma
Yu-Hang YE ; Hao-Yang XIN ; Jia-Li LI ; Ning LI ; Si-Yuan PAN ; Long CHEN ; Jing-Yue PAN ; Zhi-Qiang HU ; Peng-Cheng WANG ; Chu-Bin LUO ; Rong-Qi SUN ; Jia FAN ; Jian ZHOU ; Zheng-Jun ZHOU ; Shao-Lai ZHOU
Clinical and Molecular Hepatology 2024;30(4):914-928
Background:
Intrahepatic cholangiocarcinoma (ICC) is a highly desmoplastic tumor with poor prognosis even after curative resection. We investigated the associations between the composition of the ICC stroma and immune cell infiltration and aimed to develop a stromal-immune signature to predict prognosis in surgically treated ICC.
Patients and methods:
We recruited 359 ICC patients and performed immunohistochemistry to detect α-smooth muscle actin (α-SMA), CD3, CD4, CD8, Foxp3, CD68, and CD66b. Aniline was used to stain collagen deposition. Survival analyses were performed to detect prognostic values of these markers. Recursive partitioning for a discrete-time survival tree was applied to define a stromal-immune signature with distinct prognostic value. We delineated an integrated stromal-immune signature based on immune cell subpopulations and stromal composition to distinguish subgroups with different recurrence-free survival (RFS) and overall survival (OS) time.
Results:
We defined four major patterns of ICC stroma composition according to the distributions of α-SMA and collagen: dormant (α-SMAlow/collagenhigh), fibrogenic (α-SMAhigh/collagenhigh), inert (α-SMAlow/collagenlow), and fibrolytic (α-SMAhigh/collagenlow). The stroma types were characterized by distinct patterns of infiltration by immune cells. We divided patients into six classes. Class I, characterized by high CD8 expression and dormant stroma, displayed the longest RFS and OS, whereas Class VI, characterized by low CD8 expression and high CD66b expression, displayed the shortest RFS and OS. The integrated stromal-immune signature was consolidated in a validation cohort.
Conclusion
We developed and validated a stromal-immune signature to predict prognosis in surgically treated ICC. These findings provide new insights into the stromal-immune response to ICC.
9.To compare the efficacy and incidence of severe hematological adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia.
Xiao Shuai ZHANG ; Bing Cheng LIU ; Xin DU ; Yan Li ZHANG ; Na XU ; Xiao Li LIU ; Wei Ming LI ; Hai LIN ; Rong LIANG ; Chun Yan CHEN ; Jian HUANG ; Yun Fan YANG ; Huan Ling ZHU ; Ling PAN ; Xiao Dong WANG ; Gui Hui LI ; Zhuo Gang LIU ; Yan Qing ZHANG ; Zhen Fang LIU ; Jian Da HU ; Chun Shui LIU ; Fei LI ; Wei YANG ; Li MENG ; Yan Qiu HAN ; Li E LIN ; Zhen Yu ZHAO ; Chuan Qing TU ; Cai Feng ZHENG ; Yan Liang BAI ; Ze Ping ZHOU ; Su Ning CHEN ; Hui Ying QIU ; Li Jie YANG ; Xiu Li SUN ; Hui SUN ; Li ZHOU ; Ze Lin LIU ; Dan Yu WANG ; Jian Xin GUO ; Li Ping PANG ; Qing Shu ZENG ; Xiao Hui SUO ; Wei Hua ZHANG ; Yuan Jun ZHENG ; Qian JIANG
Chinese Journal of Hematology 2023;44(9):728-736
Objective: To analyze and compare therapy responses, outcomes, and incidence of severe hematologic adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia (CML) . Methods: Data of patients with chronic phase CML diagnosed between January 2006 and November 2022 from 76 centers, aged ≥18 years, and received initial flumatinib or imatinib therapy within 6 months after diagnosis in China were retrospectively interrogated. Propensity score matching (PSM) analysis was performed to reduce the bias of the initial TKI selection, and the therapy responses and outcomes of patients receiving initial flumatinib or imatinib therapy were compared. Results: A total of 4 833 adult patients with CML receiving initial imatinib (n=4 380) or flumatinib (n=453) therapy were included in the study. In the imatinib cohort, the median follow-up time was 54 [interquartile range (IQR), 31-85] months, and the 7-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.2%, 88.4%, 78.3%, and 63.0%, respectively. The 7-year FFS, PFS, and OS rates were 71.8%, 93.0%, and 96.9%, respectively. With the median follow-up of 18 (IQR, 13-25) months in the flumatinib cohort, the 2-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.4%, 86.5%, 58.4%, and 46.6%, respectively. The 2-year FFS, PFS, and OS rates were 80.1%, 95.0%, and 99.5%, respectively. The PSM analysis indicated that patients receiving initial flumatinib therapy had significantly higher cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) and higher probabilities of FFS than those receiving the initial imatinib therapy (all P<0.001), whereas the PFS (P=0.230) and OS (P=0.268) were comparable between the two cohorts. The incidence of severe hematologic adverse events (grade≥Ⅲ) was comparable in the two cohorts. Conclusion: Patients receiving initial flumatinib therapy had higher cumulative incidences of therapy responses and higher probability of FFS than those receiving initial imatinib therapy, whereas the incidence of severe hematologic adverse events was comparable between the two cohorts.
Adult
;
Humans
;
Adolescent
;
Imatinib Mesylate/adverse effects*
;
Incidence
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Antineoplastic Agents/adverse effects*
;
Retrospective Studies
;
Pyrimidines/adverse effects*
;
Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy*
;
Treatment Outcome
;
Benzamides/adverse effects*
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Leukemia, Myeloid, Chronic-Phase/drug therapy*
;
Aminopyridines/therapeutic use*
;
Protein Kinase Inhibitors/therapeutic use*
10.A prospective cohort study of long-term fasting blood glucose variability and risk of mortality in patients with type 2 diabetes.
Yi Jia CHEN ; Yu QIN ; Hao YU ; Zheng ZHU ; Chong SHEN ; Yan LU ; Ting Ting CHENG ; Ning ZHANG ; Shu Jun GU ; Jin Yi ZHOU ; Ming WU ; Jian SU
Chinese Journal of Epidemiology 2023;44(7):1099-1105
Objective: To investigate the association between long-term fasting blood glucose (FPG) variability and all-cause mortality in patients with type 2 diabetes. Methods: A total of 7 174 type 2 diabetic patients included in National Basic Public Health Service Program in Changshu of Jiangsu Province were recruited as participants. Long-term glucose variability was assessed using standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) across FPG measurements at the more than three visits. Death information were mainly obtained from the death registry system in Jiangsu. Then Cox proportional hazards regression models were used to estimate the associations of four variability indicators and all-cause mortality's hazard ratios (HRs) and their 95%CIs. Results: Among 55 058.50 person-years of the follow-up, the mean follow-up time was 7.67 years, and 898 deaths occurred during the follow-up period. After adjustment, compared with T1 group, the Cox regression model showed that HRs of T3 group in SD, CV, ARV and VIM were 1.24 (95%CI: 1.03-1.49), 1.20 (95%CI: 1.01-1.43), 1.28 (95%CI: 1.07-1.55) and 1.20 (95%CI:1.01-1.41), respectively. HRs of per 1 SD higher SD, CV, ARV and VIM were 1.13 (95%CI: 1.06-1.21), 1.08 (95%CI: 1.01-1.15), 1.05 (95%CI: 1.00-1.12) and 1.09 (95%CI: 1.02-1.16) for all-cause mortality, respectively. In the stratified analysis, age, gender, hypoglycemic agent and insulin uses had no effect on the above associations (all P for interaction >0.05). Conclusion: Long-term FPG glycemic variability was positively associated with the risk of all-cause mortality in type 2 diabetes patients.

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