Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model

Objective: To explore the risk factors of anastomotic leakage (AL) after laparoscopic anterior resection (AR) of rectal cancer and establish a nomogram prediction model.Methods: Clinical and surgical data of patients who underwent AR of rectal cancer at Sichuan Cancer Hospital from January 2017 to December 2020 were retrospectively collected. Univariate and multivariate logistic regression analyses were used to screen the independent risk factors of AL after AR. A nomogram risk prediction model was established based on the selected independent risk factors and the predictive performance of nomogram was evaluated.Results: A 1013 patients undergoing laparoscopic AR were included, of which 67 had AL, with an incidence of 6.6%. Univariate and multivariate logistic regression analyses showed that male gender, tumors distance from the anus verge of <= 5cm, tumors distance from the anus verge of 5-10cm, circumferential tumor growth, operation time >= 240min, and no diverting stoma were independent risk factors for AL after AR. A nomogram prediction model was established based on these results. The calibration curve showed that the predicted occurrence probability of the nomogram model was in good agreement with the actual occurrence probability. The area under the receiver operating characteristic (ROC) curve was 0.749.Conclusion: The nomogram prediction model based on the independent risk factors of patients undergoing AL after AR can effectively predict the probability of AL.

Automated summary

This study aimed to explore the risk factors of anastomotic leakage (AL) after laparoscopic anterior resection (AR) of rectal cancer and established a prediction model to assess its occurrence probability. By analyzing the clinical and surgical data of patients, it was found that factors such as male gender, tumor distance from the anus verge, tumor growth pattern, operation time, and whether diverting stoma was performed were associated with the occurrence of AL. The established prediction model based on these factors can effectively predict the probability of AL.