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Colorectal surveillance interval assignment based on in vivo prediction of polyp histology: impact of endoscopic
Susan G Coe1, Colleen Thomas, Julia Crook
1Division of Gastroenterology, Mayo Clinic, Jacksonville, Florida 32224, USA.
Background:
Validated training methods are needed before in vivo optical diagnosis can be used to guide colorectal cancer surveillance interval assignments.
Objectives:
To assess the impact of endoscopist training on accuracy of surveillance intervals based on in vivo optical diagnosis.
Design:
Prospective, randomized study.
Setting:
Tertiary referral center.
Patients:
A total of 1231 patients with colorectal polyps (before training, n = 577; after training, n = 654).
Interventions:
Endoscopists were randomized to either participate or not participate in two 1-hour training sessions. Endoscopists' in vivo pathology predictions were recorded for all resected polyps. The accuracy of in vivo prediction-guided surveillance intervals were compared with pathology-guided intervals as the criterion standard. Surveillance interval accuracy before and after training were analyzed.
Main Outcome Measurements:
Surveillance interval accuracy based on in vivo polyp predictions with pathology-guided intervals as criterion standard before and after a training intervention.
Results:
Optically predicted surveillance intervals for the trained group of endoscopists had an overall accuracy of 84% (242/287) before training and 82% (261/317) after training. There was little evidence to suggest that training had a meaningful impact on the accuracy of optically predicted surveillance intervals (odds ratio 1.20; 95% CI, 0.76-1.89, P = .44).
Limitations:
Limitations include small sample size, lack of endoscopist prediction confidence levels, and optional use of narrow-band imaging.
Conclusions:
Surveillance interval accuracy did not meet published thresholds (>90%) to use in vivo optical diagnosis without pathologic confirmation. Larger studies, focused specifically on the impact of training, are needed to validate methods to improve polyp diagnosis and surveillance predication accuracy.
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