Quality indicators for colonoscopy and the risk of interval cancer.

By M. Kaminski, J. Reguła, E. Kraszewska, M. Pólkowski, U. Wojciechowska, J. Didkowska, M. Zwierko, M. Rupinski, M. Nowacki, E. Butruk. New England Journal of Medicine, 2010

1,953 citations recorded by the source corpus.

Subfields: Oncology, Pulmonary and Respiratory Medicine

View Paper: https://www.semanticscholar.org/paper/3284fea2a417a26b182bc13c64e4755b2bfbf03f

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In Oncology

In Pulmonary and Respiratory Medicine

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Citations in the corpus

KVASIR: A Multi-Class Image Dataset for Computer Aided Gastrointestinal Disease Detection (2017, background): “However, the ability to detect adenomas varies between doctors, and this may eventually affect the individuals’ risk of getting colorectal cancer [19].”
Serrated Lesions of the Colorectum: Review and Recommendations From an Expert Panel (2012, background): “Second, initial studies have found that variability in detection of serrated lesions in the proximal colon is greater (73, 119) than has been reported for adenomas (149, 150), supporting a rationale for relatively close intervals to compensate for increased missing of serrated lesions.”
Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study (2019, background): “1 8 Additionally, there is evidence that with each 1.0% increase in adenoma detection rate (ADR), there is an associated 3.0% decrease in the risk of interval CRC. 9 10 However, polyps can be missed, with reported miss rates of up to 27% due to both polyp and operator characteristics.”
Performance of artificial intelligence for colonoscopy regarding adenoma and polyp detection: a meta-analysis. (2020, background): “Interval colorectal cancer (CRC) represents one of the most dismal consequences of screening colonoscopy with an incidence of 0.5 to 1 per 1000 patient-years 1,2 .”
Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model (2017, background): “30 This operator dependence leads to substantial variation between endoscopists in their effectiveness in preventing CRC with colonoscopy, 31 32 which is the fundamental goal of most colonoscopies.”
Quality Indicators for Colonoscopy (2015, background): “ADR is now designated an outcome measure because of the extensive evidence that it correlates directly with CRC and predicts effective prevention of CRC.(16,30,121) This correlation is partly because”