Objective To establish dynamic nomogram models for postoperative recurrence and survival risk of patients with AFP-negative hepatocellular carcinoma(ANHC)based on multimodal clinical data,to identify ANHC-specific prognostic biomarker combinations by integrating tumor biological characteristics and treatment response parameters through machine learning,and to provide an individualized risk assessment tool for overcoming the limitations of traditional serum biomarkers.Methods A retrospective analysis was performed for 421 ANHC patients who underwent hepatectomy in Eastern Hepatobiliary Surgery Hospital from April 2012 to December 2018,and they were randomly divided into training group with 210 patients and validation group with 211 patients.The univariate and multivariate Cox proportional-hazards regression models were used to identify independent prognostic factors and establish a nomogram model,and the receiver operating characteristic(ROC)curve,the calibration curve,and the decision curve analysis were used to assess the performance of the model.Related indicators were measured,including prealbumin(PA),white blood cell count(WBC),tumor size,and microvascular invasion.The chi-square test or the Fisher's exact test was used for comparison of categorical variables between two groups,and the independent-samples t test or the Mann-Whitney U test was used for comparison of continuous variables between two groups.Results The multivariate analysis showed that multiple tumors(hazard ratio[HR]=3.30,P<0.001),WBC(HR=1.05,P=0.005),blood glucose(HR=1.15,P=0.026),CA19-9(HR=1.17,P=0.005),and tumor size(HR=1.17,P<0.001)were independent risk factors for disease-free survival(DFS),while PA(HR=0.99,P=0.022)was a protective factor.Incomplete tumor capsule(HR=0.60,P=0.009),age(HR=1.02,P=0.035),prothrombin time(PT)(HR=1.27,P=0.023),CA19-9(HR=1.01,P<0.001),and tumor size(HR=1.15,P<0.001)were independent risk factors for overall survival(OS).The DFS nomogram achieved an AUC of 0.74(95%confidence interval[CI]:0.64-0.84)in the training group and 0.67(95%CI:0.57-0.77)in the validation group,while the OS nomogram had an AUC of 0.76(95%CI:0.64-0.88)and 0.73(95%CI:0.60-0.87),respectively.The calibration curve and the decision curve analysis showed that the models had good predictive accuracy and clinical practicability.Conclusion Preoperative indicators,including tumor number,PA,WBC,and tumor size,can effectively predict postoperative recurrence in ANHC patients,while tumor capsule integrity,age,and PT are significantly associated with OS.The nomogram models established have good performance and can provide a basis for individualized prognostic assessment.

Objective To establish dynamic nomogram models for postoperative recurrence and survival risk of patients with AFP-negative hepatocellular carcinoma(ANHC)based on multimodal clinical data,to identify ANHC-specific prognostic biomarker combinations by integrating tumor biological characteristics and treatment response parameters through machine learning,and to provide an individualized risk assessment tool for overcoming the limitations of traditional serum biomarkers.Methods A retrospective analysis was performed for 421 ANHC patients who underwent hepatectomy in Eastern Hepatobiliary Surgery Hospital from April 2012 to December 2018,and they were randomly divided into training group with 210 patients and validation group with 211 patients.The univariate and multivariate Cox proportional-hazards regression models were used to identify independent prognostic factors and establish a nomogram model,and the receiver operating characteristic(ROC)curve,the calibration curve,and the decision curve analysis were used to assess the performance of the model.Related indicators were measured,including prealbumin(PA),white blood cell count(WBC),tumor size,and microvascular invasion.The chi-square test or the Fisher's exact test was used for comparison of categorical variables between two groups,and the independent-samples t test or the Mann-Whitney U test was used for comparison of continuous variables between two groups.Results The multivariate analysis showed that multiple tumors(hazard ratio[HR]=3.30,P<0.001),WBC(HR=1.05,P=0.005),blood glucose(HR=1.15,P=0.026),CA19-9(HR=1.17,P=0.005),and tumor size(HR=1.17,P<0.001)were independent risk factors for disease-free survival(DFS),while PA(HR=0.99,P=0.022)was a protective factor.Incomplete tumor capsule(HR=0.60,P=0.009),age(HR=1.02,P=0.035),prothrombin time(PT)(HR=1.27,P=0.023),CA19-9(HR=1.01,P<0.001),and tumor size(HR=1.15,P<0.001)were independent risk factors for overall survival(OS).The DFS nomogram achieved an AUC of 0.74(95%confidence interval[CI]:0.64-0.84)in the training group and 0.67(95%CI:0.57-0.77)in the validation group,while the OS nomogram had an AUC of 0.76(95%CI:0.64-0.88)and 0.73(95%CI:0.60-0.87),respectively.The calibration curve and the decision curve analysis showed that the models had good predictive accuracy and clinical practicability.Conclusion Preoperative indicators,including tumor number,PA,WBC,and tumor size,can effectively predict postoperative recurrence in ANHC patients,while tumor capsule integrity,age,and PT are significantly associated with OS.The nomogram models established have good performance and can provide a basis for individualized prognostic assessment.

Objective:To analyze clinical features of aortoesphageal fistula (AEF) patients with massive upper gastrointestinal hemorrhage.Methods:Five AEF patients with massive upper gastrointestinal hemorrhage admitted in Peking Union Medical College Hospital from 2016 January 1st to 2019 December 31st. The clinical data, endoscopic findings, radiological manifestations, treatment and clinical outcomes were retrospectively analyzed.Results:Among 5 patients, 4 were males, 1 was female with an average age of (58±8) years old. The underlying conditions were atherosclerosis ( n=4), hypertension ( n=3), hyperlipidemia ( n=1); 2 cases had aortic aneurysm stent implantation and 1 case of rheumatic heart disease had valve replacement. All 5 patients were complicated with hematemesis and hypovolemic shock, and 4 cases had sentinel hemorrhage. Contrast-enhanced CT or CT angiography of the aorta showed thicken esophageal wall, local esophageal discontinuity, aortic aneurysm, gas around the aortic stent and contrast agent spilling over. The gastroscopy showed esophageal depression lesions, deep ulcers, mucosal erosion with bleeding. Conservative therapy and endoscopic hemostasis failed, 2 patients died without surgical intervention; 3 patients underwent emergency surgeries, 2 survived and 1 died perioperatively. Conclusions:Aortoesophageal fistula is in lack of specific clinical manifestations but is highly in mortality. Therefore CT and gastrocopic examination should be performed for suspected patients, early diagnosis and surgical treatment are the key to save patients′ lives.

Objective To investigate the optimal method for synthesizing thiolated doxorubicin .Methods Thiolated doxorubi-cin was synthesized through two different methods .Doxorubicin was reacted with 2-iminothiolane (2-IT) and S-acetylthioglycolic acid N-hydroxysuccinimide ester (SATA),respectively.The synthesized thiolated doxorubicin was further characterized by HPLC and MS -ESI techniques .Several factors including molar ratios as well as reaction time were evaluated .Results The results showed that thiolat-ed doxorubicin could be synthesized via both of the two methods successfully .Thiolated doxorubicin could be stable when doxorubicin was reacted with SATA .But the crude thiolated doxorubicin could be cyclized easily when doxorubicin was reacted with 2-IT.Conclu-sion Thiolated doxorubicin prepared with SATA is more feasible than that with 2-IT.