Construction Of A Nomogram For Predicting Anastomotic Fistula After Minimally Invasive McKeown Radical Resection Of Esophageal Cancer

Background:Esophageal cancer is one of the malignant tumors with high incidence rate and high mortality in the world.Surgery is the main treatment method for esophageal cancer.Minimally invasive McKeown radical resection of esophageal cancer is one of the main surgical methods for esophageal cancer.anastomotic fistula is a common complication after minimally invasive McKeown radical resection of esophageal cancer,which increases patients’ short-term mortality and seriously affects postoperative recovery of patients.At present,relevant researches at home and abroad show that the risk factors for anastomotic fistula after minimally invasive McKeown radical resection of esophageal cancer are still highly controversial,and there is a lack of models and tools that can accurately predict the probability of anastomotic fistula occurrence.The aim of this study is to explore the independent risk factors of anastomotic fistula after minimally invasive McKeown radical resection of esophageal cancer,and to construct a nomogram for predicting anastomotic fistula based on this,in order to help clinical doctors identify high-risk patients with anastomotic fistula and intervene as soon as possible.Methods:A retrospective analysis was conducted on 815 patients who underwent minimally invasive McKeown radical resection of esophageal cancer at Qilu Hospital of Shandong University from April 2014 to August 2022.Randomly allocate all datasets in a 3:1 ratio to the training or validation cohort,and divide patients into the anastomotic fistula group and the non anastomotic fistula group for analysis based on the occurrence of anastomotic fistula.Use hypothesis testing for univariate analysis on the training cohort,use multivariate logistic regression analysis to identify independent risk factors,construct a predictive nomogram for anastomotic fistula based on independent risk factors,and conduct internal validation on the validation cohort.Results:The incidence of anastomotic fistula in 815 patients included was 16.6%(135/815).Univariate analysis and multivariate logistic regression analysis identified seven independent risk factors,namely,older age,high BMI,diabetes,chronic obstructive pulmonary disease,low preoperative serum albumin level,new adjuvant treatment and long operation time.Through analysis,the area under the receiver operating characteristic(ROC)curve(AUC)of the training and validation cohorts were 0.771 and 0.715,respectively,indicating good predictive accuracy of the prediction model.The Hosmer-Lemeshow(HL)test showed good fit of the calibration curve,indicating good consistency between the predicted probability and the actual probability of the model.Decision curve analysis(DCA)shows that the constructed predictive nomogram has good clinical utility.Conclusion:This study constructed a predictive nomogram for postoperative anastomotic fistula after minimally invasive McKeown radical resection of esophageal cancer based on seven independent risk factors explored.Statistical testing and internal validation confirmed that the predictive nomogram had good predictive effect and strong clinical practicality,which can help clinical doctors identify high-risk patients with anastomotic fistula before surgery and take corresponding intervention measures to reduce the occurrence of anastomotic fistula before surgery,bescides,close monitoring should be conducted after surgery to detect and actively treat anastomotic fistula as soon as possible,in order to reduce the adverse effects of anastomotic fistula.