Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
2175 participants
OBSERVATIONAL
2008-09-15
2017-07-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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CASE_CONTROL
PROSPECTIVE
Study Groups
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Normal colonoscopy
No interventions assigned to this group
Colonic polyps
No interventions assigned to this group
Colorectal cancer patients
No interventions assigned to this group
Breast & Prostate Cancer patients
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* asymptomatic, 50-75 year old, without personal or family history of CRC/polyps
* asymptomatic, 40-75 year old, known personal or first-degree family history of either CRC or polyps
For Cancer group:
* any patient with diagnosis of colorectal cancer
* any patient with diagnosis of prostate cancer
* any patient with diagnosis of breast cancer
Exclusion Criteria
* hematochezia
* inflammatory bowel disease
* on anticoagulation for reasons other than atrial fibrillation
* significant co-morbidities
For Cancer group:
* already had neoadjuvant treatment at time of urine collection
* no invasive cancer at time of urine collection
18 Years
90 Years
ALL
No
Sponsors
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University of Alberta
OTHER
Responsible Party
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Principal Investigators
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Haili Wang, MD FRCS(C)
Role: STUDY_DIRECTOR
University of Alberta
Locations
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University of Alberta
Edmonton, Alberta, Canada
Countries
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References
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Eisner R, Greiner R, Tso V, Wang H, Fedorak RN. A machine-learned predictor of colonic polyps based on urinary metabolomics. Biomed Res Int. 2013;2013:303982. doi: 10.1155/2013/303982. Epub 2013 Nov 7.
Other Identifiers
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514
Identifier Type: OTHER
Identifier Source: secondary_id
MTI-2008
Identifier Type: -
Identifier Source: org_study_id
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