CC BY-NC-ND 4.0 · Endosc Int Open 2021; 09(05): E716-E726
DOI: 10.1055/a-1381-7181
Original article

Training methods in optical diagnosis and characterization of colorectal polyps: a systematic review and meta-analysis

Samuel C.L. Smith
1   Institute of Translational Medicine and Institute of Immunology and Immunotherapy, University of Birmingham, United Kingdom
,
Keith Siau
2   University Hospitals Birmingham NHS Trust, Birmingham, United Kingdom
,
Rosanna Cannatelli
1   Institute of Translational Medicine and Institute of Immunology and Immunotherapy, University of Birmingham, United Kingdom
3   Department of Gastroenterology, Spedali Civili and University of Milan, Italy
,
Giulio Antonelli
4   Endoscopy Unit, Nuovo Regina Margherita Hospital, Rome, Italy
,
Uday N. Shivaji
1   Institute of Translational Medicine and Institute of Immunology and Immunotherapy, University of Birmingham, United Kingdom
5   National Institute for Health Research (NIHR) Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Trust, United Kingdom
,
Subrata Ghosh
1   Institute of Translational Medicine and Institute of Immunology and Immunotherapy, University of Birmingham, United Kingdom
5   National Institute for Health Research (NIHR) Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Trust, United Kingdom
,
John R. Saltzman
6   Department of Gastroenterology, Brigham and Women Hospital, Harvard Medical School, Boston, Massachusetts, United States
,
Cesare Hassan
4   Endoscopy Unit, Nuovo Regina Margherita Hospital, Rome, Italy
,
Marietta Iacucci
1   Institute of Translational Medicine and Institute of Immunology and Immunotherapy, University of Birmingham, United Kingdom
5   National Institute for Health Research (NIHR) Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Trust, United Kingdom
› Author Affiliations

Abstract

Background and study aims Correct optical diagnosis of colorectal polyps is crucial to implement a resect and discard strategy. Training methods have been proposed to reach recommended optical diagnosis thresholds. The aim of our study was to present a systematic review and meta-analysis on optical diagnosis training.

Methods PubMed/Medline and Cochrane databases were searched between 1980 and October 2019 for studies reporting outcomes on optical diagnosis training of colorectal polyps. The primary outcome was optical diagnosis accuracy compared to histological analysis pre-training and post-training intervention. Subgroup analyses of experienced/trainee endoscopists, training methods, and small/diminutive polyps were included.

Results Overall, 16 studies met inclusion criteria, analyzing the impact of training on 179 endoscopists. Pre-training accuracy was 70.3 % (6416/9131 correct diagnoses) whereas post-training accuracy was 81.6 % (7416/9213 correct diagnoses) (risk ratio [RR] 1.17; 95 % confidence interval [CI]: 1.09–1.24, P < 0.001). In experienced endoscopists, accuracy improved from 69.8 % (3771/5403 correct diagnoses) to 82.4 % (4521/5485 correct diagnoses) (RR 1.20; 95 % CI: 1.11–1.29, P < 0.001). Among trainees, accuracy improved from 69.6 % (2645/3803 correct diagnoses) to 78.8 % (2995/3803 correct diagnoses) (RR 1.14; 95 % CI 1.06–1.24, P < 0.001). In the small/diminutive polyp subgroup, accuracy improved from 68.1 % (3549/5214 correct diagnoses) to 77.1 % (4022/5214 correct diagnoses) in (RR 1.16 95 % CI 1.08–1.24 P < 0.001). On meta-regression analysis, the improvement in accuracy did not differ between computerized vs. didactic training approaches for experienced (P = 0.792) and trainee endoscopists (P = 0.312).

Conclusions Optical diagnosis training is effective in improving accuracy of histology prediction in colorectal polyps. Didactic and computer-based training show comparable effectiveness in improving diagnostic accuracy.

Supplementary material



Publication History

Received: 12 August 2020

Accepted: 09 December 2020

Article published online:
22 April 2021

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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