Potential roles of artificial intelligence learning and faecal immunochemical testing for prioritisation of colonoscopy in anaemia. (3rd February 2019)

• Record Type: Journal Article
• Authors: Ayling, Ruth M.; Lewis, Stephen J.; Cotter, Finbarr
• Is Part Of: British journal of haematology. Volume 185:Number 2(2019)
• Page Start: 311
• Page End: 316
• Publication Date: 2019-02-03
• Subjects: iron deficiency -- anaemia -- colorectal carcinoma -- faecal immunochemical test -- AI learning; Hematology -- Periodicals; Blood -- Diseases -- Periodicals; 616.15
• DOI: 10.1111/bjh.15776
• Languages: English
• ISSNs: 0007-1048

Abstract

Summary: Iron deficiency anaemia (IDA) is the most common cause of anaemia and a frequent indication for colonoscopy, although the prevalence of colorectal cancer (CRC) in IDA is low. Measurement of faecal haemoglobin by immunochemical techniques (FIT) is used to detect symptomatic patients. We studied FIT in patients with anaemia attending a gastroenterology clinic in Plymouth and looked at an artificial intelligence (AI) learning algorithm (ColonFlag™) in these patients, together with a cohort who had undergone colonoscopy for IDA in London. Of 592 patients referred on the basis of haemoglobin concentration, 21 (3.5%) had CRC. Using ColonFlag™, rather than haemoglobin concentration, in combination with symptoms, would have resulted in prioritisation of 304 patients for urgent referral rather than 592. One CRC would have been missed but might have been detected by FIT, which was not available in this case. In patients aged <55 years in whom the incidence of CRC is low, 15 rather than 109 patients would have been prioritised for urgent referral with no cancers missed. FIT has a high negative predictive value in IDA so its use may enable some patients to avoid investigation and AI learning may be a more useful trigger than haemoglobin concentration for urgent referral for colonoscopy.