1.Serum concentrations of LH, FSH, estradiol and testosterone in healthy infants
Chai JI ; Binhua PAN ; Xu WANG ; Zhengyan ZHAO ;
Chinese Journal of Endocrinology and Metabolism 2000;0(06):-
0.05). Conclusion Peaks of serum gonadotropin and sex hormone concentrations are reached at 2~4 months of age and sexual dimorphism is shown, suggesting that in boy and girl infants, different mechanisms may be involved in regulating the development of gonads.
2.Prognosis and influencing factors of liver transplantation for hepatocellular carcinoma using steatotic donor liver: a multicenter study
Mengfan YANG ; Rui WANG ; Binhua PAN ; Renyi SU ; Siyi DONG ; Xiao XU ; Shusen ZHENG ; Xuyong WEI
Chinese Journal of Digestive Surgery 2022;21(2):237-248
Objective:To investigate the prognosis and influencing factors of liver transplantation (LT) for hepatocellular carcinoma (HCC) using steatotic donor liver.Methods:The retrospective cohort study was conducted. The clinicopathological data of 152 pairs of donors and the corresponding recipients undergoing LT for HCC in the two medical centers [89 pairs in Shulan (Hangzhou) Hospital and 63 pairs in the First Affiliated Hospital of Zhejiang University School of Medicine] from January 2015 to December 2019 were collected. Of 152 donors, there were 131 males and 21 females, aged (48±12)years, and there were 130 cases with liver mild steatosis and 22 cases with liver moderate steatosis. Of 152 recipients, there were 138 males and 14 females, aged (52±9)years. Observation indicators: (1) follow-up, overall survival and tumor recurrence free survival of recipients; (2) influencing factors for overall survival and tumor recurrence free survival of recipients; (3) construction and validation of nomogram prediction model for overall survival and tumor recurrence free survival of recipients. Follow-up was conducted using outpatient examination and telephone interview to detect survival and tumor recurrence of recipients up to December 2020. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( IQR). Count data were described as absolute numbers. The Kaplan-Meier method was used to calculate the survival time and draw survival curve, and the Log-Rank test was used for survival analysis. The COX regression model was used for univariate and multivariate analysis. The independent risk factors were brought into the R 3.6.2 software to construct nomogram prediction model and draw the receiver operating characteristic (ROC) curve. The accuracy and discrimination of the nomogram prediction model were evaluated using the area under curve (AUC) and the calibration curve. Results:(1) Follow-up, overall survival and tumor recurrence free survival of recipients. All the 152 recipients undergoing LT for HCC using steatotic donor liver were followed up for 45.8(27.6)months, with the overall survival time and tumor recurrence free survival time of 36.5(32.3)months and 30.4(34.6)months. The 1-year, 3-year overall survival rates and tumor recurrence free rates of the 152 recipients were 73.4%, 55.8% and 62.2%, 43.4%, respectively. (2) Influencing factors for overall survival and tumor recurrence free survival of recipients. Results of univariate analysis showed that the donor liver cold ischemia time (CIT), the donor liver warm ischemia time (WIT), graft-to-recipient weight ratio (GRWR), ABO compatibility, recipient body mass index (BMI), recipient tumor diameter, recipient tumor number, recipient tumor differentiation degree, recipient preoperative alpha fetoprotein (AFP) were related factors influencing the overall survival of recipients ( hazard ratio=6.26, 1.90, 2.47, 4.08, 0.55, 5.16, 3.62, 5.28, 2.65, 95% confidence interval as 3.01?13.03, 1.07?3.38, 1.36?4.49, 2.07?8.03, 0.31?0.98, 2.56?10.42, 1.95?6.72, 1.60?17.42, 1.48?5.01, P<0.05) and the donor liver CIT, GRWR, ABO compatibility, recipient tumor diameter, recipient tumor number, recipient tumor differentiation degree, recipient preoperative AFP were related factors influencing the tumor recurrence free survival of recipients ( hazard ratio=4.24, 2.53, 4.05, 3.39, 3.10, 5.19, 2.63, 95% confidence interval as 2.50?7.21, 1.54?4.17, 2.12?7.72, 2.04?5.62, 1.91?5.03, 2.04?13.18, 1.61?4.30, P<0.05). Results of multivariate analysis showed that donor liver CIT ≥8 hours, GRWR ≥2.5%, recipient tumor diameter ≥8 cm and recipient preoperative AFP ≥400 μg/L were independent risk factors influencing the overall survival of recipients ( hazard ratio=4.21, 2.58, 4.10, 2.27, 95% confidence interval as 1.98?8.96, 1.24?5.35, 1.35?12.43, 1.13?4.56, P<0.05) and donor liver CIT ≥8 hours, GRWR ≥2.5%, recipient tumor diameter ≥8 cm, recipient tumor number ≥3 and recipient preoperative AFP ≥400 μg/L were independent risk factors influencing the tumor recurrence free survival of recipients ( hazard ratio=3.37, 2.63, 2.42, 2.12, 2.22, 95% confidence interval as 1.70?6.67, 1.40?4.96, 1.04?5.66, 1.08?4.18, 1.26?3.90, P<0.05). (3) Construction and validation of nomogram prediction model for overall survival and tumor recurrence free survival of recipients. The donor live CIT, GRWR, recipient tumor diameter, recipient preoperative AFP were used to construct nomogram prediction model for overall survival of recipients and the donor liver CIT, GRWR, recipient tumor diameter, recipient tumor number, recipient preoperative AFP were used to construct nomogram prediction model for tumor recurrence free survival of recipients. The ROC curve showed that the AUC of the nomogram prediction model for overall survival of recipients was 0.84 (95% confidence interval as 0.76?0.92, P<0.05), with the optimal diagnostic value as 7.3 and the specificity and sensitivity as 87.6% and 70.0%. The AUC of the nomogram prediction model for tumor recurrence free survival of recipients was 0.79 (95% confidence interval as 0.71?0.87, P<0.05), with the optimal diagnostic value as 5.8 and the specificity and sensitivity as 97.4% and 52.5%. The calibration curve showed that the nomogram prediction model had good distinction for high risk recipients in overall survival and tumor recurrence free survival. Conclusion:Donor liver CIT ≥8 hours, GRWR ≥2.5%, recipient tumor diameter ≥8 cm and recipient preoperative AFP ≥400 μg/L are independent risk factors influencing the overall survival of recipients who underwent LT for HCC using steatotic donor liver and donor liver CIT ≥8 hours, GRWR ≥2.5%, recipient tumor diameter ≥8 cm, recipient tumor number ≥ 3 and recipient preoperative AFP ≥400 μg/L are independent risk factors influencing the tumor recurrence free survival of recipients.
3.Predictive effect of liver fibrosis score and other factors on the prognosis of liver transplantation for liver cancer
Binhua PAN ; Xuyong WEI ; Zhikun LIU ; Li ZHUANG ; Jianhui LI ; Mengfan YANG ; Zhisheng ZHOU ; Shusen ZHENG ; Xiao XU
Chinese Journal of Organ Transplantation 2021;42(3):131-135
Objective:To explore the value of aspartate aminotransferase(AST)and platelet (PLT)ratio index(APRI)in the prognosis of liver transplantation(LT)for hepatocellular carcinoma and establish a nomogram model for evaluating its clinical application potential.Methods:From January 2015 to December 2019, retrospective review was conducted for clinical data of LT for hepatocellular carcinoma(HCC)at First Affiliated Hospital of Zhejiang University School of Medicine and Shulan(Hangzhou)Hospital(601 cases). They were randomized into two groups of modeling (399 cases)and validation(202 cases)and then divided into low and high APRI groups according to the APRI value at Month 1 post-transplantation. The independent risk factors of recurrence and prognosis post-LT were screened in modeling group using univariate and multivariate Cox regression analyses and were further used for constructing a nomogram prediction model. The receiver operating characteristic curve(ROC)and survival curve were utilized for verifying the accuracy of nomogram prediction model.Results:Univariate and multivariate Cox regression analyses revealed that independent risk factors for the prognosis of HCC-LT included cold ischemic time(CIT) >8 h, beyond Hangzhou criteria, surgical bleeding volume >1 000 ml and APRI >1.5. The AUC of HCC-LT recurrence prediction model was 0.734(95%CI: 0.681~0.787)and 0.749(95%CI: 0.671~0.817)in modeling and validation groups; the AUC of HCC-LT mortality prediction model was 0.735(95%CI: 0.679~0.790)and 0.758(95%CI: 0.682~0.834)in modeling and validation groups.Conclusions:APRI>1.5 is an independent risk factor for postoperative recurrence and mortality after HCC-LT. The nomogram prediction model based upon CIT, Hangzhou criteria, intraoperative bleeding volume and APRI can effectively predict the recurrence and overall survival of LT for HCC.