Prediction model for anastomotic leakage after laparoscopic rectal cancer resection
Enesh Shiwakoti, Jianning Song, Jun Li, Shanshan Wu, Zhongtao Zhang
Abstract
OBJECTIVE: This study was performed to identify risk factors for anastomotic leakage (AL) and combine these factors to create a prediction model for the risk of AL after laparoscopic rectal cancer resection. METHODS: This retrospective study involved 185 patients with rectal cancer who underwent laparoscopic resection from March 2012 to February 2017. Five risk factors were analyzed by multivariate analysis. A prediction model was established by combining the risk factors from the multivariate analysis, and the accuracy of the model was evaluated by a receiver operating characteristic curve. RESULTS: The overall AL rate was 17.84%. The multivariate analysis identified the following independent risk factors for AL: high body mass index (odds ratio [OR], 3.009; 95% confidence interval [CI], 1.127-7.125), preoperative radiochemotherapy (OR, 3.778; 95% CI, 1.168-12.219), larger tumor size (OR, 2.710; 95% CI, 1.119-6.562), and longer surgical time (OR, 2.476; 95% CI, 1.033-5.932). We established a prediction model that can evaluate the risk of AL by determining the predictive probability. The area under the curve for the model's predictive performance was 0.70 (95% CI, 0.598-0.795). CONCLUSION: A prediction model was created to predict the risk of AL after laparoscopic rectal cancer resection.