Colon Cancer Clinical Trial
Official title:
Comparison of the Diagnostic Potential of Colonoscopy, and Artificial Intelligence-assisted Fecal Microbiome Testing for Colon Cancer
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.
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. ;
| Status | Clinical Trial | Phase | |
|---|---|---|---|
| Active, not recruiting |
NCT05551052 -
CRC Detection Reliable Assessment With Blood
|
||
| Completed |
NCT03457454 -
Reducing Rural Colon Cancer Disparities
|
||
| Recruiting |
NCT06006390 -
CEA Targeting Chimeric Antigen Receptor T Lymphocytes (CAR-T) in the Treatment of CEA Positive Advanced Solid Tumors
|
Phase 1/Phase 2 | |
| Active, not recruiting |
NCT04088955 -
A Digimed Oncology PharmacoTherapy Registry
|
||
| Recruiting |
NCT06010862 -
Clinical Study of CEA-targeted CAR-T Therapy for CEA-positive Advanced/Metastatic Malignant Solid Tumors
|
Phase 1 | |
| Terminated |
NCT01347645 -
Irinotecan Plus E7820 Versus FOLFIRI in Second-Line Therapy in Patients With Locally Advanced or Metastatic Colon or Rectal Cancer
|
Phase 1/Phase 2 | |
| Completed |
NCT03390907 -
Hybrid APC Assisted EMR for Large Colon Polyps
|
N/A | |
| Recruiting |
NCT03175224 -
APL-101 Study of Subjects With NSCLC With c-Met EXON 14 Skip Mutations and c-Met Dysregulation Advanced Solid Tumors
|
Phase 2 | |
| Completed |
NCT04079478 -
The AID Study: Artificial Intelligence for Colorectal Adenoma Detection
|
||
| Active, not recruiting |
NCT04057274 -
Acute Effect of modeRate-intensity aerOBIc Exercise on Colon Cancer Cell Growth
|
N/A | |
| Recruiting |
NCT03190941 -
Administering Peripheral Blood Lymphocytes Transduced With a Murine T-Cell Receptor Recognizing the G12V Variant of Mutated RAS in HLA-A*11:01 Patients
|
Phase 1/Phase 2 | |
| Not yet recruiting |
NCT05147545 -
Impact of Exercise and Hyperlipidic Meal on Free Circulating DNA in Patients With Metastatic Colonic Cancer and Healthy Subjects
|
N/A | |
| Recruiting |
NCT05026268 -
The Laparoscopic Right Colectomy With Intracoroporeal Anastomosis
|
N/A | |
| Not yet recruiting |
NCT03277235 -
Effect of a Resilience Model-Based Care Plan in Newly Diagnosed Colorectal Cancer Patients
|
N/A | |
| Active, not recruiting |
NCT02959541 -
PK/PD Investigation of Calciumfolinat in Blood, Tumor and Adjacent Mucosa in Patient With Colon Cancer
|
N/A | |
| Active, not recruiting |
NCT02730702 -
Colon Cancer Risk-stratification Via Optical Analysis of Rectal Ultrastructure
|
||
| Completed |
NCT02810652 -
Perioperative Geriatrics Intervention for Older Cancer Patients Undergoing Surgical Resection
|
N/A | |
| Recruiting |
NCT02577627 -
Multi-Indication, Retrospective Oncological Study to Validate the Accuracy in Predicting TTP by PrediCare in Patients Under SOC
|
N/A | |
| Terminated |
NCT02628535 -
Safety Study of MGD009 in B7-H3-expressing Tumors
|
Phase 1 | |
| Recruiting |
NCT02526836 -
Complete Mesocolic Excision With Central Vessel Ligation Compared With Conventional Surgery for Colon Cancer
|
Phase 2/Phase 3 |