A Predictive Model for Anastomotic Complications After Sphincter-Preserving Surgery for Rectal Cancer: Integrating Clinical and Anatomical Risk Factors.

Abstract

Background: Rectal cancer surgery presents a technical challenge due to the intricate anatomy of the pelvis, contributing to an increased risk of postoperative complications.

Objective: The aim of this study was to assess the prognostic value of clinical and anatomical factors in predicting anastomotic complications after sphincter-preserving surgery for rectal cancer.

Design: Retrospective analysis.

Settings: Taipei Medical University Hospital.

Patients: A total of 527 patients with rectal cancer.

Interventions: Robotic or laparoscopic total mesorectal excision between 2012 and 2023.

Main outcome measures: Preoperative clinical parameters and magnetic resonance imaging-derived anatomical measurements were subjected to multivariate analysis to develop a predictive model for postoperative anastomotic complications.

Results: Over a mean period of 66.2 (6-149) months, the incidence of anastomotic complications following sphincter-preserving surgery was 15.8%. Multivariate logistic regression identified six predictors of anastomotic complications: tumor-to-anal verge distance (p = 0.003), interspinous diameter (p = 0.030), clinical N stage (p = 0.047), angle α (p = 0.015), carcinoembryonic antigen level (p = 0.046), and American Society of Anesthesiologists classification (p = 0.015). These variables were incorporated into the final model, with an area under the receiver operating characteristic curve of 0.70 (95% confidence interval: 0.60-0.78). The top three predictors of anastomotic complications were tumor-to-anal verge distance, interspinous diameter, and clinical N stage.

Limitations: All data were obtained from a single institution, the study was retrospective, all pelvimetric measurements were obtained manually (introducing the possibility of interobserver variability and measurement error), and the parameters analyzed were limited to two-dimensional measurements.

Conclusions: These findings highlight the role of clinical variables and pelvimetry in predicting anastomotic complications after minimally invasive rectal surgery. The developed regression model is a practical tool for refining preoperative planning and informed decision-making. See Video Abstract.