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Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records

BACKGROUND: A valid risk prediction model for colorectal cancer (CRC) could be used to identify individuals in the population who would most benefit from CRC screening. We evaluated the potential for information derived from a panel of blood tests to predict a diagnosis of CRC from 1 month to 3 year...

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Autores principales: Goshen, Ran, Mizrahi, Barak, Akiva, Pini, Kinar, Yaron, Choman, Eran, Shalev, Varda, Sopik, Victoria, Kariv, Revital, Narod, Steven A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5379154/
https://www.ncbi.nlm.nih.gov/pubmed/28253525
http://dx.doi.org/10.1038/bjc.2017.53
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author Goshen, Ran
Mizrahi, Barak
Akiva, Pini
Kinar, Yaron
Choman, Eran
Shalev, Varda
Sopik, Victoria
Kariv, Revital
Narod, Steven A
author_facet Goshen, Ran
Mizrahi, Barak
Akiva, Pini
Kinar, Yaron
Choman, Eran
Shalev, Varda
Sopik, Victoria
Kariv, Revital
Narod, Steven A
author_sort Goshen, Ran
collection PubMed
description BACKGROUND: A valid risk prediction model for colorectal cancer (CRC) could be used to identify individuals in the population who would most benefit from CRC screening. We evaluated the potential for information derived from a panel of blood tests to predict a diagnosis of CRC from 1 month to 3 years in the future. METHODS: We abstracted information on 1755 CRC cases and 54 730 matched cancer-free controls who had one or more blood tests recorded in the electronic records of Maccabi Health Services (MHS) during the period 30–180 days before diagnosis. A scoring model (CRC score) was constructed using the study subjects' blood test results. We calculated the odds ratio for being diagnosed with CRC after the date of blood draw, according to CRC score and time from blood draw. RESULTS: The odds ratio for having CRC detected within 6 months for those with a score of four or greater (vs three or less) was 7.3 (95% CI: 6.3–8.5) for men and was 7.8 (95% CI: 6.7–9.1) for women. CONCLUSIONS: Information taken from routine blood tests can be used to predict the risk of being diagnosed with CRC in the near future.
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spelling pubmed-53791542018-03-28 Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records Goshen, Ran Mizrahi, Barak Akiva, Pini Kinar, Yaron Choman, Eran Shalev, Varda Sopik, Victoria Kariv, Revital Narod, Steven A Br J Cancer Molecular Diagnostics BACKGROUND: A valid risk prediction model for colorectal cancer (CRC) could be used to identify individuals in the population who would most benefit from CRC screening. We evaluated the potential for information derived from a panel of blood tests to predict a diagnosis of CRC from 1 month to 3 years in the future. METHODS: We abstracted information on 1755 CRC cases and 54 730 matched cancer-free controls who had one or more blood tests recorded in the electronic records of Maccabi Health Services (MHS) during the period 30–180 days before diagnosis. A scoring model (CRC score) was constructed using the study subjects' blood test results. We calculated the odds ratio for being diagnosed with CRC after the date of blood draw, according to CRC score and time from blood draw. RESULTS: The odds ratio for having CRC detected within 6 months for those with a score of four or greater (vs three or less) was 7.3 (95% CI: 6.3–8.5) for men and was 7.8 (95% CI: 6.7–9.1) for women. CONCLUSIONS: Information taken from routine blood tests can be used to predict the risk of being diagnosed with CRC in the near future. Nature Publishing Group 2017-03-28 2017-03-02 /pmc/articles/PMC5379154/ /pubmed/28253525 http://dx.doi.org/10.1038/bjc.2017.53 Text en Copyright © 2017 Cancer Research UK http://creativecommons.org/licenses/by-nc-sa/4.0/ From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Molecular Diagnostics
Goshen, Ran
Mizrahi, Barak
Akiva, Pini
Kinar, Yaron
Choman, Eran
Shalev, Varda
Sopik, Victoria
Kariv, Revital
Narod, Steven A
Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records
title Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records
title_full Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records
title_fullStr Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records
title_full_unstemmed Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records
title_short Predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records
title_sort predicting the presence of colon cancer in members of a health maintenance organisation by evaluating analytes from standard laboratory records
topic Molecular Diagnostics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5379154/
https://www.ncbi.nlm.nih.gov/pubmed/28253525
http://dx.doi.org/10.1038/bjc.2017.53
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