[Clinical value of nomogram model in evaluating the prognosis of cholangiocarcinoma after interventional therapy].

Objective: To investigate the clinical value and efficacy of the nomogram model in evaluating the prognosis of cholangiocarcinoma after interventional therapy. Methods: The clinical data of 259 patients with cholangiocarcinoma who received interventional therapy at the First Affiliated Hospital of zhengzhou University from January 2014 to June 2021 were retrospectively analyzed, including 148 males and 111 females, aged from 26 to 91 (65±12) years. They were randomly divided into a training group (181 cases) and a validation group (78 cases) in a ratio of 7∶3. Cox regression analysis was performed in the training group, independent risk factors affecting the prognosis of patients were screened, and a nomogram for 6-month, 1-year, and 2-year survival was constructed. The performance of the nomogram was analyzed by calculating the area under the receiver operating characteristic curve (AUC) value, calibration curve, and decision curve, and the predictive efficacy of the model was evaluated in the validation group. Results: There was no significant difference in baseline data between the training group and the validation group, which was comparable. Regression analysis showed that T stage (T2: HR=0.147,95%CI: 0.077-0.281;T3: HR=0.207,95%CI: 0.122-0.351;T4: HR=0.864,95%CI: 0.537-1.393), tumor diameter (17-33 mm: HR=0.201,95%CI: 0.119-0.341;≥33 mm: HR=0.795,95%CI: 0.521-1.211) and differentiation degree(middle differentiation: HR=3.318,95%CI: 2.082-5.289;highly differentiation: HR=1.842,95%CI: 1.184-2.867) were risk factors affecting the prognosis of interventional therapy for cholangiocarcinoma. The AUC values of the survival curve prediction models were generally consistent between the training and validation groups, and the AUC values of the training group at 6 months, 1 year, and 2 years were 0.925 (95%CI: 0.888-0.963), 0.921 (95%CI: 0.877-0.964) and 0.974 (95%CI: 0.957-0.993), respectively. In the validation group, the 6-month, 1-year, and 2-year AUC values were 0.951 (95%CI: 0.911-0.991), 0.917 (95%CI: 0.857-0.977) and 0.848 (95%CI: 0.737-0.959), respectively, and the AUC values were all greater than 0.8, suggesting that the nomogram had better discrimination ability. The calibration curves of the prediction models of the two groups were basically consistent, and the shape of the calibration curves at 6 months and 1 year fitted the ideal curve, while the fitting degree of the calibration curves at 2 years was relatively poor. The decision curve showed the high clinical utility of this nomogram in predicting the 6-month, 1-year survival of patients with cholangiocarcinoma. Conclusions: T stage, tumor diameter, and differentiation are independent risk factors affecting the prognosis of patients with interventional cholangiocarcinoma, and the nomogram model proposed in this study has good distinguishing ability and exact clinical value for prognosis evaluation.

Glucagon-like peptide-1 receptor agonists and fracture risk: a network meta-analysis of randomized clinical trials.

Our network meta-analysis analyzed the effects of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) on fracture risk. By combining data from randomized controlled trials, we found that GLP-1 RAs were associated with a decreased bone fracture risk, and exenatide is the best option agent with regard to the risk of fracture. This study is registered with PROSPERO (CRD42018094433). INTRODUCTION: Data on the effects of GLP-1 RAs on fracture risk are conflicted. This study aimed to analyze the available evidence on the effects of GLP-1 RAs on fracture risk in type 2 diabetes mellitus patients. METHODS: Electronic databases were searched for relevant published articles, and unpublished studies presented at ClinicalTrials.gov were searched for relevant clinical data. All analyses were performed with STATA 12.0 and R software (Version 3.4.4). We estimated the risk ratio (RR) and 95% confidence interval (CI) by combining RRs for fracture effects of included trials. RESULTS: There were 54 eligible random control trials (RCTs) with 49,602 participants, including 28,353 patients treated with GLP-1 RAs. Relative to placebo, exenatide (RR, 0.17; 95% CI 0.03-0.67) was associated with lowest risk of fracture among other GLP-1 RAs. Exenatide had the highest probability to be the safest option with regard to the risk of fracture (0.07 ‰), followed by dulaglutide (1.04%), liraglutide (1.39%), albiglutide (5.61%), lixisenatide (8.07%), and semaglutide (18.72%). A statistically significant inconsistency was observed in some comparisons. CONCLUSION: The Bayesian network meta-analysis suggests that GLP-1 RAs were associated with a decreased bone fracture risk compared to users of placebo or other anti-hyperglycemic drugs in type 2 diabetes mellitus patients, and exenatide is the best option agent with regard to the risk of fracture.