1.Effect of chemotherapy regimen CCLG-ALL-2008 on children with TEL/AML1 fusion gene positive of acute lymphoblastic leukemia
Jing GAO ; Shaoyan HU ; Jun LU ; Hailong HE ; Yi WANG ; Wenli ZHAO ; Jianqin LI ; Jie LI ; Peifang XIAO ; Junjie FAN ; Yihuan CHAI
Journal of Clinical Pediatrics 2017;35(5):325-330
Objective To evaluate the predictive role of TEL/AML1 fusion gene in protocol CCLG-ALL-2008 and to identify relevant factors influencing the outcome of ALL with TEL/AML1 fusion gene. Methods Ninety-nine patients with ALL harboring TEL/AML1 fusion gene (positive) and 329 cases without any specific fusion genes (negative) at diagnosis of B-lineage ALL from June 2008 to December 2014 were enrolled and their clinical and biological features were analyzed. Following-up ended in October 2015, the survival status was calculated by K-M curve and prognostic factors were analyzed by COX model. Results There were no differences between the two groups in age, white blood cell at the diagnostic stage, and treatment responses at 4 time points, namely, prednisone good response on day 8, M3 status of BM on D15, and the minimal residual disease (MRD) more than 1.0×10-3 on day 33 and 12th week. During the follow-up period, the relapse rate was lower in the positive group than that in the negative group (14/99 vs 69/329), the mortality rate of the negative group was twice of that in the positive group (55/329 vs 8/99). The five-year overall survival (OS) rate, relapse-free survival (RFS) rate and event-free survival (EFS) rate of the positive group were (86.1 ± 4.9)%, (80.7 ± 5.1)% and (78.9 ± 5.1)%, respectively, and (79 ±2.8)%, (72± 3.1)%, and (69.6+ 3.1)% for the negative group as well. COX regression analysis indicated that relapse and MRD level at the 12th week were independent prognostic factors on OS, RFS, and EFS (P<0.05) for the two groups. Conclusions TEL/AML1 fusion gene could be regarded as a relatively good indicator of risks in ALL children treated by CCLG-ALL-2008 protocol. ALL patients with TEL/AML1 are recommended to receive more intensive therapy including hematopoietic stem cell transplantation when the patients were high level of MRD on the 12th week after treatment.
2.Study on related factors and effect relationship of hyperuricemia in health check-up participants
Lin ZHUO ; Siting CHEN ; Yihuan GAO ; Hang LU ; Xiuying WANG ; Lang ZHUO ; Jingqiu CUI
Chinese Journal of Endocrinology and Metabolism 2022;38(10):880-886
Objective:To investigate the influencing factors of hyperuricemia(HUA) and explore early intervention of metabolic diseases.Methods:A total of 70 523 participants were selected from the database of check-ups in 2016. Univariate analysis and logistic regression analysis were used to identify related factors of HUA. Correspondence analysis was performed for the aggregation of different levels of uric acid(UA) and related factors. The mediating effect of mean blood pressure(MBP) between abnormal metabolic indicators and abnormal renal function was tested.Results:The age, sex, occupation, body mass index(BMI), systolic blood pressure, diastolic blood pressure, blood urea nitrogen(BUN), creatinine(Cr), estimated glomerular filtration rate(eGFR), fasting plasma glucose(FPG), total cholesterol(TC), triacylglycerol(TG), high density lipoprotein-cholesterol(HDL-C), low density lipoprotein-cholesterol, plasma viscosity were significantly related to HUA( P<0.001). Logistic regression analysis showed that youth, male, hypertension, TC, TG, and Cr were risk factors for HUA, while HDL-C was a protective factor for HUA( P<0.001). Correspondence analysis showed that during the gradual increase of UA, TC was the first to appear abnormal, followed by hypertension and TG, and the increase of Cr appeared last. Mediating effect showed that in changes of UA, the mediating effects of MBP on TC, TG, and HDL-C were 36.35%, 12.63%, and 9.41%, respectively. In changes of eGFR, the mediating effects of MBP on TC, TG and HDL-C were 30.20%, 27.70%, and 6.13%, respectively. Conclusions:UA is positively correlated with blood pressure, TC, and TG, and inversely with HDL-C. TC and TG have an impact on renal impairment, in which MBP plays a mediating role.
3.Analysis on the implementation effect of single disease payment policy for day surgery based on difference-in-differences model
Hongcheng ZHANG ; Jianqiang PAN ; Hang LU ; Yihuan GAO ; Yunxin KONG ; Chunxia MIAO ; Lang ZHUO
Chinese Journal of Hospital Administration 2023;39(5):332-336
Objective:To analyze the implementation effect of single disease payment policy for day surgery (hereinafter referred to as the policy), for references for the reform of medical insurance payment.Methods:By collecting the information of inpatients from 2017 to 2019 in a tertiary hospital, the research group took patients with colorectal benign tumor and nodular goitre as the policy implementation group and the control group respectively. 2017-2018 was the pre implementation stage of the policy, and 2019 was the post implementation stage of the policy. The difference-in-differences (DID) model was used to analyze the changes in indicators such as length of stay and hospitalization expenses after policy implementation, under whether the policy is implemented or not, as well as before or after policy implementation.Results:A total of 2 419 patients were included, including 927 patients with nodular goiter in the control group and 1 492 patients with colorectal benign tumors in the policy implementation group (688 patients before the policy implementation and 804 patients after the policy implementation). The results of DID showed that the hospital days for patients with colorectal benign tumor decreased by 56.53%, the hospitalization expenses decreased by 26.51%, the out-of-pocket expenses decreased by 26.66%, the treatment expenses increased by 11.96%, the drug expenses decreased by 50.29% and the consumables expenses decreased by 20.23% after the implementation of the policy.Conclusions:The implementation of the policy could reduce length of stay, hospitalization expenses and out-of-pocket expenses, optimize the structure of hospitalization expenses, improve the efficiency of hospital diagnosis and treatment, and help the hospital realize its transformation from a size expansion to a quality and benefit expansion.