Single Versus Second Observer vs Artificial Intelligence to Increase the ADENOMA Detection Rate of Colonoscopy—A Network Analysis

Background and Aims Screening colonoscopy has significantly contributed to the reduction of the incidence of colorectal cancer (CRC) and its associated mortality, with adenoma detection rate (ADR) as the quality marker. To increase the ADR, various solutions have been proposed including the utilizat...

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Bibliographic Details
Published in:Digestive diseases and sciences 2024-04, Vol.69 (4), p.1380-1388
Main Authors: Gangwani, Manesh Kumar, Haghbin, Hossein, Ishtiaq, Rizwan, Hasan, Fariha, Dillard, Julia, Jaber, Fouad, Dahiya, Dushyant Singh, Ali, Hassam, Salim, Shaharyar, Lee-Smith, Wade, Sohail, Amir Humza, Inamdar, Sumant, Aziz, Muhammad, Hart, Benjamin
Format: Article
Language:English
Subjects:
Adenoma - diagnosis
Artificial Intelligence
Biochemistry
Colonoscopy
Colonoscopy - methods
Colorectal Neoplasms - diagnosis
Gastroenterology
Hepatology
Humans
Medicine
Medicine & Public Health
Meta-analysis
Network Meta-Analysis
Odds Ratio
Oncology
Original Article
Transplant Surgery
Tumors
Citations: Items that this one cites
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Summary:Background and Aims Screening colonoscopy has significantly contributed to the reduction of the incidence of colorectal cancer (CRC) and its associated mortality, with adenoma detection rate (ADR) as the quality marker. To increase the ADR, various solutions have been proposed including the utilization of Artificial Intelligence (AI) and employing second observers during colonoscopies. In the interest of AI improving ADR independently, without a second observer, and the operational similarity between AI and second observer, this network meta-analysis aims at evaluating the effectiveness of AI, second observer, and a single observer in improving ADR. Methods We searched the Medline, Embase, Cochrane, Web of Science Core Collection, Korean Citation Index, SciELO, Global Index Medicus, and Cochrane. A direct head-to-head comparator analysis and network meta-analysis were performed using the random-effects model. The odds ratio (OR) was calculated with a 95% confidence interval (CI) and p -value 
ISSN:0163-2116
1573-2568
1573-2568
DOI:10.1007/s10620-024-08341-9