Prediction of findings at screening colonoscopy using a machine learning algorithm based on complete blood counts (ColonFlag)

Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient information and complete blood cell counts (CBC) to identify individuals at elevated risk of colorectal cancer for intensified screening. The purpose of th...

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Published in:	PloS one Vol. 13; no. 11; p. e0207848
Main Authors:	Hilsden, Robert J., Heitman, Steven J., Mizrahi, Barak, Narod, Steven A., Goshen, Ran
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 27.11.2018 Public Library of Science (PLoS)
Subjects:	Algorithms Anemia Artificial intelligence Biology and Life Sciences Blood Blood tests Cancer Cancer research Cancer screening Colon Colon cancer Colonoscopy Colorectal cancer Colorectal carcinoma Data mining Diagnosis Electronic health records Endoscopy Erythrocytes Feces Gastrointestinal diseases Health care Health risks Health sciences Health screening Hospitals Inflammation Laboratories Learning algorithms Lesions Machine learning Medical records Medical research Medical screening Medical tests Medicine and Health Sciences Mortality Pathology Patient education Patients Platelets Polyps Population Population studies Preventive medicine Primary care Research and Analysis Methods Risk Risk factors Subgroups Systematic review Task forces Canada Israel Calgary Alberta Canada United Kingdom > UK Alberta Canada United States > US
ISSN:	1932-6203, 1932-6203
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Abstract	Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient information and complete blood cell counts (CBC) to identify individuals at elevated risk of colorectal cancer for intensified screening. The purpose of this study was to determine whether ColonFlag is also able to predict the presence of high risk adenomatous polyps at colonoscopy. This study was conducted at a large colon cancer screening center in Calgary, Alberta. The study population included asymptomatic individuals between the ages of 50 and 75 who underwent a screening colonoscopy between January 2013 and June 2015. All subjects had at least one CBC result within the year prior to colonoscopy. Based on age, sex, red blood cell parameters, inflammatory cells and platelets, the ColonFlag algorithm generated a score from 0 to 100. We compared the ability of the ColonFlag test result to discriminate between individuals who were found to have a high risk polyp and those with a normal colonoscopy. Among the 17,676 individuals who underwent a screening colonoscopy there were 1,014 found to have a high risk precancerous lesion (5.7%) and 60 were found to have colorectal cancer (0.3%). At a specificity of 95%, the odds ratio for a positive ColonFlag was 2.0 for those with an advanced precancerous lesion compared with those with a normal colonoscopy. The odds ratio did not vary according to patient subgroup, colorectal cancer location or stage. ColonFlag is a passive test that can use routine blood test results to help identify individuals at elevated risk for high risk precancerous polyps as well as frank colorectal cancer. These individuals may be targeted in an effort to achieve greater compliance with conventional screening tests.
AbstractList	Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient information and complete blood cell counts (CBC) to identify individuals at elevated risk of colorectal cancer for intensified screening. The purpose of this study was to determine whether ColonFlag is also able to predict the presence of high risk adenomatous polyps at colonoscopy. This study was conducted at a large colon cancer screening center in Calgary, Alberta. The study population included asymptomatic individuals between the ages of 50 and 75 who underwent a screening colonoscopy between January 2013 and June 2015. All subjects had at least one CBC result within the year prior to colonoscopy. Based on age, sex, red blood cell parameters, inflammatory cells and platelets, the ColonFlag algorithm generated a score from 0 to 100. We compared the ability of the ColonFlag test result to discriminate between individuals who were found to have a high risk polyp and those with a normal colonoscopy. Among the 17,676 individuals who underwent a screening colonoscopy there were 1,014 found to have a high risk precancerous lesion (5.7%) and 60 were found to have colorectal cancer (0.3%). At a specificity of 95%, the odds ratio for a positive ColonFlag was 2.0 for those with an advanced precancerous lesion compared with those with a normal colonoscopy. The odds ratio did not vary according to patient subgroup, colorectal cancer location or stage. ColonFlag is a passive test that can use routine blood test results to help identify individuals at elevated risk for high risk precancerous polyps as well as frank colorectal cancer. These individuals may be targeted in an effort to achieve greater compliance with conventional screening tests. Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient information and complete blood cell counts (CBC) to identify individuals at elevated risk of colorectal cancer for intensified screening. The purpose of this study was to determine whether ColonFlag is also able to predict the presence of high risk adenomatous polyps at colonoscopy. This study was conducted at a large colon cancer screening center in Calgary, Alberta. The study population included asymptomatic individuals between the ages of 50 and 75 who underwent a screening colonoscopy between January 2013 and June 2015. All subjects had at least one CBC result within the year prior to colonoscopy. Based on age, sex, red blood cell parameters, inflammatory cells and platelets, the ColonFlag algorithm generated a score from 0 to 100. We compared the ability of the ColonFlag test result to discriminate between individuals who were found to have a high risk polyp and those with a normal colonoscopy. Among the 17,676 individuals who underwent a screening colonoscopy there were 1,014 found to have a high risk precancerous lesion (5.7%) and 60 were found to have colorectal cancer (0.3%). At a specificity of 95%, the odds ratio for a positive ColonFlag was 2.0 for those with an advanced precancerous lesion compared with those with a normal colonoscopy. The odds ratio did not vary according to patient subgroup, colorectal cancer location or stage. ColonFlag is a passive test that can use routine blood test results to help identify individuals at elevated risk for high risk precancerous polyps as well as frank colorectal cancer. These individuals may be targeted in an effort to achieve greater compliance with conventional screening tests.Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient information and complete blood cell counts (CBC) to identify individuals at elevated risk of colorectal cancer for intensified screening. The purpose of this study was to determine whether ColonFlag is also able to predict the presence of high risk adenomatous polyps at colonoscopy. This study was conducted at a large colon cancer screening center in Calgary, Alberta. The study population included asymptomatic individuals between the ages of 50 and 75 who underwent a screening colonoscopy between January 2013 and June 2015. All subjects had at least one CBC result within the year prior to colonoscopy. Based on age, sex, red blood cell parameters, inflammatory cells and platelets, the ColonFlag algorithm generated a score from 0 to 100. We compared the ability of the ColonFlag test result to discriminate between individuals who were found to have a high risk polyp and those with a normal colonoscopy. Among the 17,676 individuals who underwent a screening colonoscopy there were 1,014 found to have a high risk precancerous lesion (5.7%) and 60 were found to have colorectal cancer (0.3%). At a specificity of 95%, the odds ratio for a positive ColonFlag was 2.0 for those with an advanced precancerous lesion compared with those with a normal colonoscopy. The odds ratio did not vary according to patient subgroup, colorectal cancer location or stage. ColonFlag is a passive test that can use routine blood test results to help identify individuals at elevated risk for high risk precancerous polyps as well as frank colorectal cancer. These individuals may be targeted in an effort to achieve greater compliance with conventional screening tests.
Audience	Academic
Author	Goshen, Ran Hilsden, Robert J. Mizrahi, Barak Heitman, Steven J. Narod, Steven A.
AuthorAffiliation	3 Familial Breast Cancer Research Unit, Women's College Research Institute, Women's College Hospital, Toronto, ON, Canada 2 Medial Cancer Research, Kfar Malal, Israel 5 Medial Early Sign, Kfar Malal, Israel 4 Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada 1 Departments of Medicine and Community Health Sciences, Cumming School of Medicine University of Calgary, Calgary, Alberta, Canada Singapore General Hospital, SINGAPORE
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BackLink	https://www.ncbi.nlm.nih.gov/pubmed/30481208$$D View this record in MEDLINE/PubMed
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Cites_doi	10.1093/jamia/ocv195 10.15585/mmwr.mm6608a1 10.1038/ajg.2012.161 10.1016/j.cgh.2014.01.042 10.1038/bjc.2017.53 10.1177/0969141315584694 10.1158/1055-9965.EPI-14-0744 10.1038/ajg.2017.174 10.1016/j.ypmed.2014.02.010 10.1007/s10865-015-9668-8 10.1371/journal.pone.0171759 10.1503/cmaj.151125 10.1016/j.gie.2016.09.025
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Copyright	COPYRIGHT 2018 Public Library of Science 2018 Hilsden et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2018 Hilsden et al 2018 Hilsden et al
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Snippet	Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient information...
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SubjectTerms	Algorithms Anemia Artificial intelligence Biology and Life Sciences Blood Blood tests Cancer Cancer research Cancer screening Colon Colon cancer Colonoscopy Colorectal cancer Colorectal carcinoma Data mining Diagnosis Electronic health records Endoscopy Erythrocytes Feces Gastrointestinal diseases Health care Health risks Health sciences Health screening Hospitals Inflammation Laboratories Learning algorithms Lesions Machine learning Medical records Medical research Medical screening Medical tests Medicine and Health Sciences Mortality Pathology Patient education Patients Platelets Polyps Population Population studies Preventive medicine Primary care Research and Analysis Methods Risk Risk factors Subgroups Systematic review Task forces
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Title	Prediction of findings at screening colonoscopy using a machine learning algorithm based on complete blood counts (ColonFlag)
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Volume	13
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