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

Manesh Kumar Gangwani; Hossein Haghbin; Rizwan Ishtiaq; Fariha Hasan; Julia Dillard; Fouad Jabbar; Dushyant Singh Dahiya; Hassam Ali; Shaharyar Salim; Wade Lee-Smith; Amir Sohail; Sumant Inamdar; Muhammad Aziz; Benjamin Hart

doi:10.1007/s10620-024-08341-9

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

Dig Dis Sci. 2024 Apr;69(4):1380-1388. doi: 10.1007/s10620-024-08341-9. Epub 2024 Mar 4.

Authors

Affiliations

¹ Department of Medicine, University of Toledo Medical Center, Toledo, OH, USA. gangwani.manesh@gmail.com.
² Department of Gastroenterology and Hepatology, Ascension Providence Hospital, Southfield, MI, USA.
³ Department of Medicine, St Francis Hospital and Medical Center, Hartford, CT, USA.
⁴ Department of Internal Medicine, Cooper University Hospital, Camden, NJ, USA.
⁵ Department of Medicine, University of Toledo Medical Center, Toledo, OH, USA.
⁶ Department of Internal Medicine, University of Missouri-Kansas City, Kansas City, MO, USA.
⁷ Department of Medicine, Central Michigan University College of Medicine, Mount Pleasant, MI, USA.
⁸ Department of Gastroenterology and Hepatology, East Carolina University Health, Greenville, NC, USA.
⁹ Department of Internal Medicine, Aga Khan University Hospital, Karachi, Pakistan.
¹⁰ University of Toledo Libraries, University of Toledo, Toledo, OH, USA.
¹¹ Department of General Surgery, New York University Langone Health, Long Island, NY, USA.
¹² Department of Gastroenterology and Hepatology, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
¹³ Department of Gastroenterology and Hepatology, University of Toledo Medical Center, Toledo, OH, USA.
¹⁴ Depertment of Hepatology and Gastroenterology, University of Michigan, Ann Arbor, MI, USA.

Abstract

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 < 0.05 was considered statistically significant.

Results: We analyzed 26 studies, involving 22,560 subjects. In the direct comparative analysis, AI demonstrated higher ADR (OR: 0.668, 95% CI 0.595-0.749, p < 0.001) than single observer. Dual observer demonstrated a higher ADR (OR: 0.771, 95% CI 0.688-0.865, p < 0.001) than single operator. In network meta-analysis, results were consistent on the network meta-analysis, maintaining consistency. No statistical difference was noted when comparing AI to second observer. (RR 1.1 (0.9-1.2, p = 0.3). Results were consistent when evaluating only RCTs. Net ranking provided higher score to AI followed by second observer followed by single observer.

Conclusion: Artificial Intelligence and second-observer colonoscopy showed superior success in Adenoma Detection Rate when compared to single-observer colonoscopy. Although not statistically significant, net ranking model favors the superiority of AI to the second observer.

Keywords: Adenoma detection rate; Artificial intelligence; Colorectal cancer; Second observer; Single observer.

Publication types

Meta-Analysis

MeSH terms

Adenoma* / diagnosis
Artificial Intelligence
Colonoscopy / methods
Colorectal Neoplasms* / diagnosis
Humans
Network Meta-Analysis
Odds Ratio