Establishment and application of three predictive models of anastomotic leakage after rectal cancer sphincter-preserving surgery

ARTICLE HIGHLIGHTS

Research background

With advances in medical technology, the success rate of sphincter-preserving surgery in patients with rectal cancer is increasing. However, anastomotic leakage (AL) remains a devastating complication.

Research motivation

AL significantly lowers patients’ quality of life. This study examines the elements that influence AL and establishes models to help doctors predict whether patients will develop AL, allowing the timely adoption of preventive measures.

Research objectives

This study aimed to identify the characteristics that influence AL and utilize these factors to build a prediction model for AL after sphincter-preserving surgery for rectal cancer.

Research methods

The clinical data of patients with rectal cancer who underwent sphincter-preserving surgery at our institution in the past five years were examined to analyze the factors influencing AL; nomogram, decision tree, and random forest prediction models were established; and the predictive efficacy of the three models was compared.

Research results

The factors influencing AL after sphincter-preserving surgery for rectal cancer were sex, diabetes mellitus, albumin level, tumor size, and tumor location. To predict the probability of postoperative AL, we constructed nomogram, decision tree, and random forest models.

Research conclusions

This study compared the predictive efficacy of the three prediction models. The random forest model performed the best and may be a useful alternative tool for predicting patients at a high risk of AL.

Research perspectives

Future research will include larger and more comprehensive cohorts across multiple centers, and build a more complete prediction model.