[Impact of adjuvant chemotherapy on prognosis in intrahepatic cholangiocarcinoma patients underwent radical resection].

Objectives: To investigate the clinical value of adjuvant chemotherapy(ACT) in patients with intrahepatic cholangiocarcinoma(ICC) who underwent radical resection and to explore the optimal population that can benefit from ACT. Methods: A retrospective cohort study method was adopted. The clinical and pathological data of 685 patients with ICC who underwent curative intent resection in 10 Chinese hepatobiliary surgery centers from January 2010 to December 2018 were collected;There were 355 males and 330 females. The age(M(IQR)) was 58(14) years (range: 22 to 83 years). Propensity score matching(PSM) was applied to balance the differences between the adjuvant and non-adjuvant chemotherapy groups. Log-rank test was used to compare the prognosis of the two groups of patients. A Bayesian network recurrence-free survival(RFS) prediction model was constructed using the median RFS time (14 months) as the target variable, and the importance of the relevant prognostic factors was ranked according to the multistate Birnbaum importance calculation. A survival prognostic prediction table was established to analyze the population benefiting from adjuvant chemotherapy. Results: Among 685 patients,214 received ACT and 471 did not receive ACT. A total of 124 pairs of patients were included after PSM, and patients in the ACT group had better overall survival (OS) and RFS than those in the non-ACT group(OS: 32.2 months vs. 18.0 months,P=0.003;RFS:18.0 months vs. 10.0 months,P=0.001). The area under the curve of the Bayesian network RFS prediction model was 0.7124. The results of the prognostic factors in order of importance were microvascular invasion (0.158 2),perineural invasion (0.158 2),N stage (0.155 8),T stage (0.120 9), hepatic envelope invasion (0.090 3),adjuvant chemotherapy (0.072 1), tumor location (0.057 5), age (0.042 3), pathological differentiation (0.034 0), sex (0.029 3), alpha-fetoprotein (0.028 9) and preoperative jaundice (0.008 5). A survival prediction table based on the variables with importance greater than 0.1 (microvascular invasion,perineural invasion,N stage,T staging) and ACT showed that all patients benefited from ACT (increase in the probability of RFS≥14 months from 2.21% to 7.68%), with a more significant increase in the probability of RFS≥14 months after ACT in early-stage patients. Conclusion: ACT after radical resection in patients with ICC significantly prolongs the OS and RFS of patients, and the benefit of ACT is greater in early patients.

[Analysis of related factors for gallstones related gallbladder intraepithelial neoplasia and establishment of prediction models].

Objective: To evaluate the related factors of gallstones related gallbladder intraepithelial neoplasia(GBIN) and establish the prediction models for gallstones related GBIN. Methods: The clinicopathological data of 750 patients who underwent cholecystectomy for gallstones at Department of Hepatobiliary Surgery of the First Affiliated Hospital of Xi'an Jiaotong University from January 2013 to December 2018 and the postoperative pathological examination showed chronic cholecystitis or GBIN were analyzed retrospectively,including 150 cases of gallstones with GBIN and 600 cases of gallstones with chronic cholecystitis.There were 264 males and 486 females with age of (51.3±14.5) years (range: 18 to 90 years).The related factors for gallstones related GBIN were screened by χ2 test and Logistic regression model,and the prediction models were established based on independent related factors and internal validation was conducted.The original data were randomly divided into a training cohort(526 cases) and a validation cohort(224 cases) at a ratio of 7∶3,and the nomogram and tree augmented naïve Bayes were conducted to establish the prediction model for gallstones related GBIN.The consistency index(C-index),calibration chart,area under the receiver operating characteristic curve(AUC) and confusion matrix were used to evaluate the prediction performance of the two models. Results: Univariate analysis showed that age,gallstones history(years),gallbladder size,whether the gallbladder mucosa smooth or not,whether the gallbladder wall thickened or not,gallstones diameter,and number of gallstones were related factors for the occurrence of gallstones related GBIN (χ²=19.957,8.599,9.724,9.301,8.341,15.288,9.169,all P<0.05).Multivariate analysis showed that age (OR=2.23,95%CI:1.50-3.31,P<0.01),gallbladder size (OR=2.11,95%CI:1.17-3.80,P=0.013),whether the gallbladder mucosa smooth or not (OR=1.80,95%CI=1.13-2.88,P=0.014),gallstones diameter(OR=2.98,95%CI:1.71-5.21,P<0.01),and number of gallstones (OR=2.14,95%CI=1.34-3.42,P<0.01) were independent related factors for the occurrence of gallstones related GBIN; the C-index of the nomogram in training cohort and validation cohort were 0.708 and 0.696,respectively.The AUC of the two models in training cohort were 70.60% and 70.73%,and in validation cohort were 68.14% and 67.47%,respectively.The accuracy of the two models in training cohort were 69.96% and 70.72%,and in validation cohort were 66.96% and 67.41%,respectively. Conclusion: Age,gallbladder size,whether the gallbladder mucosa smooth or not,gallstones diameter and number of gallstones are independent related factors for the occurrence of gallstones related GBIN,and the nomogram and tree augmented naïve Bayes prediction models based on the above factors can be used to predict the occurrence of GBIN.

[A prognostic model of intrahepatic cholangiocarcinoma after curative intent resection based on Bayesian network].

Objective: To examine a survival prognostic model applicable for patients with intrahepatic cholangiocarcinoma (ICC) based on Bayesian network. Methods: The clinical and pathological data of ICC patients who underwent curative intent resection in ten Chinese hepatobiliary surgery centers from January 2010 to December 2018 were collected.A total of 516 patients were included in the study.There were 266 males and 250 females.The median age(M(QR)) was 58(14) years.One hundred and sixteen cases (22.5%) with intrahepatic bile duct stones,and 143 cases (27.7%) with chronic viral hepatitis.The Kaplan-Meier method was used for survival analysis.The univariate and multivariate analysis were implemented respectively using the Log-rank test and Cox proportional hazard model.One-year survival prediction models based on tree augmented naive Bayesian (TAN) and naïve Bayesian algorithm were established by Bayesialab software according to different variables,a nomogram model was also developed based on the independent predictors.The receiver operating characteristic curve and the area under curve (AUC) were used to evaluate the prediction effect of the models. Results: The overall median survival time was 25.0 months,and the 1-,3-and 5-year cumulative survival rates was 76.6%,37.9%,and 21.0%,respectively.Univariate analysis showed that gender,preoperative jaundice,pathological differentiation,vascular invasion,microvascular invasion,liver capsule invasion,T staging,N staging,margin,intrahepatic bile duct stones,carcinoembryonic antigen,and CA19-9 affected the prognosis(χ2=5.858-54.974, all P<0.05).The Cox multivariate model showed that gender,pathological differentiation,liver capsule invasion,T stage,N stage,intrahepatic bile duct stones,and CA19-9 were the independent predictive factors(all P<0.05). The AUC of the TAN model based on all 19 clinicopathological factors was 74.5%,and the AUC of the TAN model based on the 12 prognostic factors derived from univariate analysis was 74.0%,the AUC of the naïve Bayesian model based on 7 independent prognostic risk factors was 79.5%,the AUC and C-index of the nomogram survival prediction model based on 7 independent prognostic risk factors were 78.8% and 0.73,respectively. Conclusion: The Bayesian network model may provide a relatively accurate prognostic prediction for ICC patients after curative intent resection and performed superior to the nomogram model.

[The progress on survival prediction model of gallbladder carcinoma].

Gallbladder carcinoma (GBC) is the most common malignancy of the biliary tract, radical resection is the only effective treatment for GBC at present. However, the postoperative effect is still poor. Therefore, identifying the key prognostic factors and establishing an individual and accurate survival prediction model for GBC are critical to prognosis assessment, treatment options and clinical decision support in patients with GBC. The prediction value of current commonly used TNM staging system is limited. Cox regression model is the most commonly used classical survival analysis method, but it is difficult to establish the association between prognostic variables. Nomogram and machine learning techniques including Bayesian network have been used to establish survival prediction model of GBC in recent years, which representing a certain degree of advancement, however, the model precision and clinical application still need to be further verified. The establishment of more accurate survival prediction models for GBC based on machine learning algorithm from Chinese multicenter large sample database to guide the clinical decision-making is the main research direction in the future.

[Analysis of the relationship between the number of lymph nodes examined and prognosis for curatively resected gallbladder carcinoma: a multi-institutional study].

Objective: To examine the role of the number of lymph nodes examined(NLNE) on the prognosis of patients with curatively resected gallbladder carcinoma(GBC). Methods: The clinicopathological data and prognosis of 401 patients with GBC who underwent radical surgery from six institutions of China from January 2013 to December 2017 were analyzed retrospectively. There were 153 males(38.2%) and 248 females(61.8%), with age of (62.0±10.5) years (range: 30-88 years). Fifty-three patients(22.2%) were accompanied by jaundice. All patients underwent radical resection+regional lymphadenectomy.R0 or R1 resection was confirmed by postoperative pathological examination.The different cut-off values of NLNE were determined by the X-tile software, the optimal cut-off values were identified by analyzing the relationship between different cut-off values of NLNE with survival rate. Kaplan-Meier method was used for survival analysis. Univariate and multivariate analysis were implemented respectively using the Log-rank test and Cox proportional hazard model. Results: Among the 401 patients enrolled, 135 cases (33.6%) had lymphatic metastasis, of which 98 cases were in N1 stage(24.4%) and 37 cases were in N2 stage(9.2%).A total of 2 794 NLNE were retrieved, with a median count of 6 (5).The median positive lymph nodes count was 0 (1), and the median positive lymph nodes ratio was 0 (IQR, 0-0.2). Since the 12 and 15 were determined as the cut-off values by X-tile, all patients were divided into three groups of 1-11, 12-15 and ≥16.The 3-year survival rate of the three groups was 45.2%, 74.5%, 12.0% respectively, with statistically significant difference between three groups (χ(2)=10.94, P<0.01). The results of multivariate analysis showed that NLNE was an independent prognostic factor for overall survival (P<0.05). Further analysis was performed specifically for subgroup of T stages. For T1b patients, the prognosis of the NLNE with 1-7 group was significantly better than that of the ≥8 group(χ(2)=4.610, P<0.05). For T2 patients, the prognosis of the TLNE ≥7 group was significantly better than that of 1 -6 group (χ(2)=4.287, P<0.05). For T3 and T4 patients, the prognosis of the TLNE with 12 - 15 group was significantly better than that of 1 -11 group (χ(2)=5.007, P<0.01) and ≥16 group (χ(2)=10.158, P<0.01). Conclusions: The NLNE is an independent factor affecting the prognosis of patients with GBC.For patients with stage T1b,8 lymph nodes should be retrieved; for patients with stage T2,extensive dissection of more than 6 lymph nodes can significantly improve the prognosis.For advanced patients (stages T3 and T4), extensive dissection with 12-15 lymph nodes is recommended. However, it fails to get more survival benefits by dissecting more than 16 lymph nodes.

[The survival prediction model of advanced gallbladder cancer based on Bayesian network: a multi-institutional study].

Objective: To investigate the clinical value of Bayesian network in predicting survival of patients with advanced gallbladder cancer(GBC)who underwent curative intent surgery. Methods: The clinical data of patients with advanced GBC who underwent curative intent surgery in 9 institutions from January 2010 to December 2015 were analyzed retrospectively.A median survival time model based on a tree augmented naïve Bayes algorithm was established by Bayesia Lab software.The survival time, number of metastatic lymph nodes(NMLN), T stage, pathological grade, margin, jaundice, liver invasion, age, sex and tumor morphology were included in this model.Confusion matrix, the receiver operating characteristic curve and area under the curve were used to evaluate the accuracy of the model.A priori statistical analysis of these 10 variables and a posterior analysis(survival time as the target variable, the remaining factors as the attribute variables)was performed.The importance rankings of each variable was calculated with the polymorphic Birnbaum importance calculation based on the posterior analysis results.The survival probability forecast table was constructed based on the top 4 prognosis factors. The survival curve was drawn by the Kaplan-Meier method, and differences in survival curves were compared using the Log-rank test. Results: A total of 316 patients were enrolled, including 109 males and 207 females.The ratio of male to female was 1.0∶1.9, the age was (62.0±10.8)years.There was 298 cases(94.3%) R0 resection and 18 cases(5.7%) R1 resection.T staging: 287 cases(90.8%) T3 and 29 cases(9.2%) T4.The median survival time(MST) was 23.77 months, and the 1, 3, 5-year survival rates were 67.4%, 40.8%, 32.0%, respectively.For the Bayesian model, the number of correctly predicted cases was 121(≤23.77 months) and 115(>23.77 months) respectively, leading to a 74.86% accuracy of this model.The prior probability of survival time was 0.503 2(≤23.77 months) and 0.496 8(>23.77 months), the importance ranking showed that NMLN(0.366 6), margin(0.350 1), T stage(0.319 2) and pathological grade(0.258 9) were the top 4 prognosis factors influencing the postoperative MST.These four factors were taken as observation variables to get the probability of patients in different survival periods.Basing on these results, a survival prediction score system including NMLN, margin, T stage and pathological grade was designed, the median survival time(month) of 4-9 points were 66.8, 42.4, 26.0, 9.0, 7.5 and 2.3, respectively, there was a statistically significant difference in the different points(P<0.01). Conclusions: The survival prediction model of GBC based on Bayesian network has high accuracy.NMLN, margin, T staging and pathological grade are the top 4 risk factors affecting the survival of patients with advanced GBC who underwent curative resection.The survival prediction score system based on these four factors could be used to predict the survival and to guide the decision making of patients with advanced GBC.

Effects of Rhynchophylline on relaxation and contraction of the bladder detrusor in rats.

AIM: The aim of this study was to observe the effects of Rhynchophylline (Rhy) on the relaxation and contraction of rat bladder detrusor and urodynamics and determine the changes in the tension of isolated rat bladder muscle strips. MATERIALS AND METHODS: Rats were randomly divided into four groups: sham-operated, overactive bladder (OAB) model, Rhy-treated, and the control group. Sections of urodynamic testing and electrophysiological OAB indicators of detrusor were measured. The effect of tension on the isolated rat bladder detrusor muscle strips was determined; activators and antagonists of calcium-activated potassium ion channels were detected in vitro using the tension method. The contraction of detrusor muscle strips and the antagonism of acetylcholine due to changes in muscle contraction were observed. RESULTS: The Rhy-treated group significantly decreased the maximum bladder capacity, bladder filling pressure, leak point pressure, contraction frequency, motility index (p < 0.05). The affinity index of Rhy was 4.53 ± 0.22. However, 1 µmol/L to 2 µmol/L Rhy shifts CaCl2 cumulative dose-response curves to the right in a non-parallel manner, showing a non-competitive antagonism. Rhy inhibits detrusor contraction by blocking L-type calcium channels and activating big-conductance calcium-activated potassium channels. A low concentration of Rhy can inhibit muscle contraction caused by intracellular calcium. CONCLUSIONS: Rhy plays an important role in OAB treatment and decreases effectively on sections of urodynamic testing and electrophysiological OAB indicators of detrusor.