Prediction of postoperative complications following transanal total mesorectal excision in middle and low rectal cancer: development and internal validation of a clinical prediction model.

Abstract

Purpose: The objective of this study is to develop a nomogram for the personalized prediction of postoperative complication risks in patients with middle and low rectal cancer who are undergoing transanal total mesorectal excision (taTME). This tool aims to assist clinicians in early identification of high-risk patients and in addressing preoperative risk factors to enhance surgical safety.

Methods: In this case-control study, 207 patients diagnosed with middle and low rectal cancer and undergoing taTME between February 2018 and November 2023 at The First Affiliated Hospital of Xiamen University were included. Independent risk factors for postoperative complications were analyzed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression and multifactorial logistic regression models. A predictive nomogram was constructed using R Studio.

Results: Among the 207 patients, 57 (27.5%) experienced postoperative complications. The LASSO and multifactorial logistic regression analyses identified operation time (OR = 1.010, P = 0.007), smoking history (OR = 9.693, P < 0.001), anastomotic technique (OR = 0.260, P = 0.004), and ASA score (OR = 9.077, P = 0.051) as significant predictors. These factors were integrated into the nomogram. The model's accuracy was validated through receiver operating characteristic curves, calibration curves, consistency indices, and decision curve analysis.

Conclusion: The developed nomogram, incorporating operation time, smoking history, anastomotic technique, and ASA score, effectively forecasts postoperative complication risks in taTME procedures. It is a valuable tool for clinicians to identify patients at heightened risk and initiate timely interventions, ultimately improving patient outcomes.