Evaluation of AL Prediction for Rectal Cancer

Anastomotic Leak Rectum Clinical Trial

Official title:

Evaluation of a Machine Learning Based Anastomotic Leakage Prediction Model After Anterior Resection for Rectal cancer-a Multicenter, Prospective, Randomized Controlled Study

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05610904
• Other study ID #: CHALP001
• Status: Not yet recruiting
• Phase: N/A
• Start date: December 10, 2022
• Est. completion date: October 10, 2025

Study information

• Verified date: November 2022
• Source: Changhai Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Anastomotic leakage is one of the most serious postoperative complications of low rectal cancer, with an incidence of 3%-21%. The occurrence of anastomotic leakage is related to many factors, and the occurrence of anastomotic leakage can be predicted by building a prediction model. Most of the anastomotic leakage prediction models constructed in the past are nomograms, which have limitations in the fitting of model creation. In the previous study, the center took the lead in building a random forest anastomotic leakage prediction model based on machine learning. This study intends to prospectively enroll patients with rectal cancer undergoing anterior abdominal resection and use their clinical data to prospectively verify the efficacy of the anastomotic leakage prediction model, and further improve and promote the prediction model.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 418
• Est. completion date: October 10, 2025
• Est. primary completion date: October 10, 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 75 Years

Eligibility

Inclusion Criteria:

1. Patients aged 18-75 years

2. Adenocarcinoma confirmed by pathology

3. Colonoscopy or imaging examination confirmed that the distance between the lower edge of the tumor and the anal edge was less than or equal to 12cm

4. Preoperative imaging diagnosis was cTxNxM0

5. No local complications (no obstruction, incomplete obstruction, no massive active bleeding, no perforation, abscess formation, and no invasion of adjacent organs)

6. The hematopoietic functions of heart, lung, liver, kidney and bone marrow meet the requirements of surgery and anesthesia

7. Voluntarily sign the informed consent form

Exclusion Criteria:

1. Previous history of malignant tumor

2. Simultaneous multiple primary colorectal cancer

3. Previous multiple abdominal and pelvic surgeries or extensive abdominal adhesions

4. Patients with intestinal obstruction, intestinal perforation, intestinal bleeding, etc., requiring emergency surgery

5. Patients with familial adenomatous polyposis and active inflammatory bowel disease

6. A history of severe mental illness

7. pregnant or lactating women

8. Patients with uncontrolled infection before operation

9. The investigator did not consider the patient to be eligible for the trial

Related Conditions & MeSH terms

• Anastomotic Leak
• Anastomotic Leak Rectum
• Rectal Neoplasms

Intervention

Diagnostic Test:
• Prediction model evaluation
a machine learning based anastomotic leakage prediction model

Locations

Country	Name	City	State
China	Department of Colorectal Surgery in Changhai Hospital	Shanghai	Shanghai

Sponsors (1)

Lead Sponsor	Collaborator
Changhai Hospital

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy of stoma implementation	Accuracy of stoma implementation: the number of anastomotic leakage patients with stoma and none anastomotic leakage patients without stoma to the number of total patients.	1 months after surgery
Secondary	Sensitivity and specificity in the prediction of anastomotic leakage		1 months after surgery
Secondary	Grade C leakage rate		1 months after surgery
Secondary	Preventive stoma rate		1 months after surgery
Secondary	Rate of stoma reverse		3-6 months after surgery