A Prediction Model of Anastomotic Stricture After Rectal Cancer

A Prediction Model of Anastomotic Stricture After Rectal Cancer: a Retrospective Cohort Analysis

Background: Anastomotic stricture significantly impacts patients' quality of life and long-term prognosis. However, current clinical practice lacks accurate tools for predicting anastomotic stricture. This study aimed to develop a nomogram to predict anastomotic stricture in patients with rectal cancer who have undergone anterior resection.

Methods: 1542 eligible patients will be recruited for the study. Least absolute shrinkage selection operator (Lasso) analysis will be used to preliminarily select predictors. A prediction model will be constructed using multivariate logistic regression and presented as a nomogram. The performance of the nomogram will be evaluated using receiver operating characteristic (ROC) curves, calibration diagrams, and decision curve analysis (DCA). Internal validation will be conducted by assessing the model's performance on a validation cohort.

Inclusion Criteria:

1. pathological confirmation of rectal cancer;
2. eligibility for surgical intervention;
3. undergoing first rectal cancer surgery;
4. acquisition of written informed consent from patients and their families;
5. no history of hypertrophic scar or allergic predispositions.

Exclusion Criteria:

1. absence of postoperative follow-up or anastomosis details;
2. patients subjected to Hartmann or Miles procedures;
3. emergency surgery candidates due to conditions like perforation or obstruction;
4. diagnosis of multiple primary malignancies;
5. intraoperative discovery of widespread implant metastases within the abdominal cavity;
6. severe comorbidities;
7. anastomotic recurrence of rectal cancer;
8. patients who had undergone stapled hemorrhoidopexy