An observational study in Colon Cancer, sponsored by Istituto Clinico Humanitas. Completed at 5 sites in 2 countries. Open to participants aged 40 Years to 80 Years. Per ClinicalTrials.gov, last updated 2021-02-05.
Sponsored by Istituto Clinico Humanitas · Observational
Colonoscopy is clinically used as the gold standard for detection of colon cancer (CRC) and removal of adenomatous polyps. Despite the success of colonoscopy in reducing cancer-related deaths, there exists a disappointing level of adenomas missed at colonoscopy. "Back-to-back" colonoscopies have indicated significant miss rates of 27% for small adenomas (\< 5 mm) and 6% for adenomas of more than 10 mm in diameter. Studies performing both CT colonography and colonoscopy estimate that the colonoscopy miss rate for polyps over 10 mm in size may be as high as 12%. The clinical importance of missed lesions should be emphasized because these lesions may ultimately progress to CRC.
Limitations in human visual perception and other human biases such as fatigue, distraction, level of alertness during examination increases such recognition errors and way of mitigating them may be the key to improve polyp detection and further reduction in mortality from CRC. In the past years, a number of CAD systems for detection of polyps from endoscopy images have been described. However, the benefits of traditional CAD technologies in colonoscopy appear to be contradictory, therefore they should be improved to be ultimately considered useful. Recent advances in artificial intelligence (AI), deep learning (DL), and computer vision have shown potential to assist polyp detection during colonoscopy.
Average experienced endoscopists (each having performed \<2000 screening colonoscopies) will perform the endoscopic procedure.
1,485 studies on the registry are indexed under Colonic Neoplasms; 362 are open to participants now.
This study's enrollment of 700 is above the median of 262 across 363 observational studies indexed under Colonic Neoplasms.
Browse Colonic Neoplasms studies →Istituto Clinico Humanitas is the lead sponsor of 279 studies on the registry; 71 are open to participants now.
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Based on the observed prevalence of adenomas (35%) among patients undergoing colonoscopies at our center within the last 12 months, a sample size of 322 subjects per arm could allow for a 90% power to show the non-inferiority (primary end-point) of the AI-aided arm by excluding that the one-side 95% CI will exclude a difference of 10% in favour of the standard group. Such sample size will also have a 80% power to detect as statistical significant (α=0.05; two-sided test) a 10% absolute increase in the detection rate of adenomas in the AI-aided arm (secondary end-point).
Performing a sub-stratification according to operator experience, we will planning to enroll the 322 subjects per arm performed by experts and 322 subjects per arm performed by average operator.
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Exclusion Criteria:
Artificial intelligence colonoscopy
Device: AI
White light colonoscopy
Artificial intelligence colonoscopy
Non-inferiority of AI-aided colonoscopy in terms of ADR
The proportion of participants with at least one adenoma (per-patient analysis).
Time frame: 5 Months
Plan to share: No
No publications or documents are linked to this record.
Ran from Feb 2020 to primary completion in Dec 2020, 10 months.
Of 126 non-industry observational studies under Colonic Neoplasms, half reached primary completion within 54 months of starting (the median), counting those still running; a quarter within 23 and three quarters within 127. This study's 10 months is below that.
Counting every sponsor, half of 148 studies reached it within 51 months; a quarter within 27 and three quarters within 127.
How these figures are worked out, and which studies are left out of them.
This study is completed, as verified in Dec 2020. You cannot join it, but the record below documents what was studied.
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