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.

Objective A retrospective study was conducted by developing prediction models to evaluate the association between hematological indexes, their changes during neoadjuvant chemoradiotherapy (NCRT), and tumor pathological response in patients with locally advanced rectal cancer. Methods The clinical data of 202 patients who received NCRT and radical surgery in Sichuan Cancer Hospital were retrospectively analyzed. Univariate and logistic multivariate regression analyses were used to identify hematological indexes with predictive significance. The independent risk factors were imported into the R software, and a nomogram prediction model was developed. The bootstrap method and ROC curve were used to evaluate the discriminative degree of the model. Results Univariate analysis demonstrated age, tumor diameter, preoperative T, distance from tumor to the anal verge, CEA before NCRT, preoperative CEA, lymphocyte changes, platelet changes, and pathology of rectal cancer after NCRT were associated. Multivariate analysis demonstrated that age, tumor distance from the anus, preoperative CEA, lymphocyte changes, and platelet changes were independent risk factors. The independent risk factors were imported into the R software to construct a nomogram model. The area under the ROC was 0.76, and the slope of the calibration curve of the nomogram was close to 1. Conclusion A low preoperative CEA level, a young age, a high tumor from the anal verge, the maintenance of circulating lymphocyte level, and a decreased platelet level after NCRT are important factors for favorable outcomes after NCRT. Developing a nomogram prediction model with good discrimination and consistency can provide some guidance for predicting pathological responses after NCRT.