Evaluation of AL Prediction for Rectal Cancer

• Sponsor: Changhai Hospital (Other)
• Overall Status: Not yet recruiting
• CT.gov ID: NCT05610904
• Collaborator: (none)
• Enrollment: 418
• Location: 1
• Arms: 2
• Anticipated Duration (Months): 34
• Patients Per Site Per Month: 12.3

Study Details

Study Description

Brief 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.

Condition or Disease	Intervention/Treatment	Phase
Anastomotic Leak Rectum	Diagnostic Test: Prediction model evaluation	N/A

Study Design

• Study Type: Interventional
• Anticipated Enrollment: 418 participants
• Allocation: Randomized
• Intervention Model: Parallel Assignment
• Masking: Single (Participant)
• Primary Purpose: Prevention
• Official Title: Evaluation of a Machine Learning Based Anastomotic Leakage Prediction Model After Anterior Resection for Rectal cancer-a Multicenter, Prospective, Randomized Controlled Study
• Anticipated Study Start Date: Dec 10, 2022
• Anticipated Primary Completion Date: Oct 10, 2024
• Anticipated Study Completion Date: Oct 10, 2025

Arms and Interventions

Arm	Intervention/Treatment
No Intervention: Surgeon evaluation
Experimental: Surgeon combining with model evaluation	Diagnostic Test: Prediction model evaluation; a machine learning based anastomotic leakage prediction model

Outcome Measures

Primary Outcome Measures

1. Accuracy of stoma implementation [1 months after surgery]

   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.

Secondary Outcome Measures

1. Sensitivity and specificity in the prediction of anastomotic leakage [1 months after surgery]

2. Grade C leakage rate [1 months after surgery]

3. Preventive stoma rate [1 months after surgery]

4. Rate of stoma reverse [3-6 months after surgery]

Eligibility Criteria

Criteria

• Ages Eligible for Study: 18 Years to 75 Years
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No

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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Department of Colorectal Surgery in Changhai Hospital	Shanghai	Shanghai	China	200433

Sponsors and Collaborators

• Changhai Hospital

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

• Responsible Party: Wei Zhang, professor, Changhai Hospital
• ClinicalTrials.gov Identifier: NCT05610904
• Other Study ID Numbers: CHALP001
• First Posted: Nov 9, 2022
• Last Update Posted: Nov 9, 2022
• Last Verified: Nov 1, 2022

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No
• Keywords provided by Wei Zhang, professor, Changhai Hospital: Anastomotic Leak; rectal cancer; machine learning
• Additional relevant MeSH terms: Rectal Neoplasms; Anastomotic Leak

Study Results

No Results Posted as of Nov 9, 2022