search
Back to results

Evaluation of the Diagnostic Potential of Artificial Intelligence-assisted Fecal Microbiome Testing for Colon Cancer

Primary Purpose

Colon Cancer, Microbiota, Colonoscopy

Status
Recruiting
Phase
Not Applicable
Locations
Turkey
Study Type
Interventional
Intervention
Artificial Intelligence-assisted Fecal Microbiome Testing
Colonoscopy
Sponsored by
Istanbul Medipol University Hospital
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Colon Cancer focused on measuring Microbiome, Colon cancer, Colonoscopy, Artificial intelligence, Screening test

Eligibility Criteria

18 Years - 70 Years (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria: over 18 years not pregnant not meeting any of the exclusion criteria Voluntary consent form signer * Indications for colonoscopy: Colorectal cancer or adenomatous polyp in first-degree relatives Patients followed for more than 8 years with ulcerative colitis, Crohn's Disease, or individuals with a history of hereditary polyposis or non-polyposis syndrome. In these groups, the screening procedure should be started from the age of 40. It is a population-based screening that begins at age 50 and ends at age 70 for all men and women (50 and 70 years will be included). However, especially in this group of patients; Male patients presenting with iron deficiency anemia Female patients over 40 years of age presenting with iron deficiency anemia Patients with positive occult blood in stool in screening programs Patients presenting with rectal bleeding Patients with defecation irregularity, weight loss Exclusion Criteria: under 18 years old Pregnant or planning to become Have another known diagnosis of gastrointestinal disease Abdominal surgery other than appendectomy or hysterectomy history Psychiatric comorbidity Chronic diseases that will affect the microbiome (cancer, diabetes, cardiovascular disease, liver diseases, neurological diseases, etc.) Use of drugs that may affect digestive function (including use in the last 4 weeks), probiotics, narcotic analgesics, lactulose (prebiotics) in the 4 weeks before the study Patients taking dietary supplements will not be included in the study.

Sites / Locations

  • Medipol University Esenler HospitalRecruiting

Arms of the Study

Arm 1

Arm Type

Experimental

Arm Label

Colonoscopy

Arm Description

Fecal samples will be obtained from patients who are enrolled for colonoscopy procedures for the suspicion of colon cancer.

Outcomes

Primary Outcome Measures

The diagnostic accuracy of the AI-assisted fecal microbiome testing in detecting colon cancer compared to colonoscopy
The diagnostic accuracy of the AI-assisted fecal microbiome testing in detecting colon cancer, as measured by sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC-ROC).

Secondary Outcome Measures

Full Information

First Posted
March 6, 2023
Last Updated
March 21, 2023
Sponsor
Istanbul Medipol University Hospital
Collaborators
Bozyaka Training and Research Hospital, Tepecik Training and Research Hospital, SB Istanbul Education and Research Hospital, Bursa City Hospital, Izmir Metropolitan Municipality Esrefpasa Hospital
search

1. Study Identification

Unique Protocol Identification Number
NCT05795725
Brief Title
Evaluation of the Diagnostic Potential of Artificial Intelligence-assisted Fecal Microbiome Testing for Colon Cancer
Official Title
Comparison of the Diagnostic Potential of Colonoscopy, and Artificial Intelligence-assisted Fecal Microbiome Testing for Colon Cancer
Study Type
Interventional

2. Study Status

Record Verification Date
February 2023
Overall Recruitment Status
Recruiting
Study Start Date
May 1, 2023 (Anticipated)
Primary Completion Date
February 29, 2024 (Anticipated)
Study Completion Date
May 31, 2024 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Istanbul Medipol University Hospital
Collaborators
Bozyaka Training and Research Hospital, Tepecik Training and Research Hospital, SB Istanbul Education and Research Hospital, Bursa City Hospital, Izmir Metropolitan Municipality Esrefpasa Hospital

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes

5. Study Description

Brief Summary
The goal of this clinical trial is to evaluate the diagnostic potential of Artificial Intelligence-assisted Fecal Microbiome Testing for the diagnosis of colon cancer. The main question it aims to answer is: • Is Artificial Intelligence-assisted Fecal Microbiome Testing a reliable screening test for colon cancer? Participants will be asked to provide fecal samples to be analyzed with next-generation sequencing techniques. If there is a comparison group: Researchers will compare the diagnostic performance of AI-assisted Fecal Microbiome Testing with colonoscopy to see the correlation between the results of both interventions.
Detailed Description
Colon cancer, also known as colorectal cancer, is the third most commonly diagnosed cancer worldwide and the second leading cause of cancer deaths. In the United States alone, it is estimated that there will be approximately 149,500 new cases and 52,980 deaths from colorectal cancer in 2021. However, if detected early, it is highly treatable and curable. Currently, the gold standard for colon cancer screening is a colonoscopy, which involves the insertion of a flexible tube with a camera into the rectum to examine the colon for signs of cancer or precancerous growths called polyps. While effective, this procedure is invasive, uncomfortable, and can be costly. As a result, many people delay or avoid colon cancer screening, which can lead to delayed detection and worse outcomes. Fecal microbiome testing is a promising alternative to colonoscopy as a screening tool for colon cancer. The human gut is home to trillions of bacteria that play a critical role in maintaining our health, and research has shown that changes in the gut microbiome can be associated with the development of colon cancer. Artificial Intelligence-assisted fecal microbiome testing involves analyzing the composition of the gut microbiome using advanced algorithms and machine learning techniques to identify patterns that are indicative of colon cancer. This non-invasive, low-cost, and convenient screening test has the potential to significantly increase colon cancer screening rates and reduce the number of deaths from this disease. By identifying individuals at high risk of colon cancer at an early stage, Artificial Intelligence-assisted fecal microbiome testing can lead to earlier intervention and better outcomes. Therefore, the diagnostic potential of AI-assisted fecal microbiome testing for colon cancer is a highly relevant and important area of research.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Colon Cancer, Microbiota, Colonoscopy
Keywords
Microbiome, Colon cancer, Colonoscopy, Artificial intelligence, Screening test

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Model Description
Fecal samples will be obtained from patients who are enrolled for colonoscopy for the clinical suspicion of colon cancer
Masking
None (Open Label)
Masking Description
The patients will be blinded to the microbiome results for the study period. The gastroenterologists will be blinded to microbiome results. The microbiome researchers will be blinded to colonoscopy results The statisticians will be blinded to both intervention results until the end of patient enrollment
Allocation
N/A
Enrollment
1000 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
Colonoscopy
Arm Type
Experimental
Arm Description
Fecal samples will be obtained from patients who are enrolled for colonoscopy procedures for the suspicion of colon cancer.
Intervention Type
Diagnostic Test
Intervention Name(s)
Artificial Intelligence-assisted Fecal Microbiome Testing
Intervention Description
Next-generation sequencing of fecal samples and artificial intelligence analysis of test results
Intervention Type
Procedure
Intervention Name(s)
Colonoscopy
Intervention Description
Colonoscopy procedure
Primary Outcome Measure Information:
Title
The diagnostic accuracy of the AI-assisted fecal microbiome testing in detecting colon cancer compared to colonoscopy
Description
The diagnostic accuracy of the AI-assisted fecal microbiome testing in detecting colon cancer, as measured by sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC-ROC).
Time Frame
2 weeks

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Maximum Age & Unit of Time
70 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria: over 18 years not pregnant not meeting any of the exclusion criteria Voluntary consent form signer * Indications for colonoscopy: Colorectal cancer or adenomatous polyp in first-degree relatives Patients followed for more than 8 years with ulcerative colitis, Crohn's Disease, or individuals with a history of hereditary polyposis or non-polyposis syndrome. In these groups, the screening procedure should be started from the age of 40. It is a population-based screening that begins at age 50 and ends at age 70 for all men and women (50 and 70 years will be included). However, especially in this group of patients; Male patients presenting with iron deficiency anemia Female patients over 40 years of age presenting with iron deficiency anemia Patients with positive occult blood in stool in screening programs Patients presenting with rectal bleeding Patients with defecation irregularity, weight loss Exclusion Criteria: under 18 years old Pregnant or planning to become Have another known diagnosis of gastrointestinal disease Abdominal surgery other than appendectomy or hysterectomy history Psychiatric comorbidity Chronic diseases that will affect the microbiome (cancer, diabetes, cardiovascular disease, liver diseases, neurological diseases, etc.) Use of drugs that may affect digestive function (including use in the last 4 weeks), probiotics, narcotic analgesics, lactulose (prebiotics) in the 4 weeks before the study Patients taking dietary supplements will not be included in the study.
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Varol TUNALI, Dr.
Phone
00905556303231
Email
varoltunali@gmail.com
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Varol TUNALI, Dr.
Organizational Affiliation
Celal Bayar University Faculty of Medicine Parasitology Department
Official's Role
Principal Investigator
Facility Information:
Facility Name
Medipol University Esenler Hospital
City
Istanbul
State/Province
Other (Non U.s.)
ZIP/Postal Code
34230
Country
Turkey
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Naciye Cigdem Arslan, MD
Phone
05313890975
First Name & Middle Initial & Last Name & Degree
Naciye Cigdem Arslan

12. IPD Sharing Statement

Learn more about this trial

Evaluation of the Diagnostic Potential of Artificial Intelligence-assisted Fecal Microbiome Testing for Colon Cancer

We'll reach out to this number within 24 hrs