Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects

Abstract Background The aim was to improve upon an existing blood-based colorectal cancer (CRC) test directed to high-risk symptomatic patients, by developing a new CRC classifier to be used with a new test embodiment. The new test uses a robust assay format—electrochemiluminescence immunoassays—to...

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Main Authors: Lisa J. Croner, Roslyn Dillon, Athit Kao, Stefanie N. Kairs, Ryan Benz, Ib J. Christensen, Hans J. Nielsen, John E. Blume, Bruce Wilcox
Format: Article
Language:English
Published: BMC 2017-07-01
Series:Clinical Proteomics
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12014-017-9163-z
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spelling doaj-1dd7c8c3e82645e28c30c9ec3bba285f2020-11-24T23:19:45ZengBMCClinical Proteomics1542-64161559-02752017-07-0114111210.1186/s12014-017-9163-zDiscovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjectsLisa J. Croner0Roslyn Dillon1Athit Kao2Stefanie N. Kairs3Ryan Benz4Ib J. Christensen5Hans J. Nielsen6John E. Blume7Bruce Wilcox8Applied Proteomics, IncApplied Proteomics, IncApplied Proteomics, IncApplied Proteomics, IncApplied Proteomics, IncDepartment of Surgical Gastroenterology 360, Hvidovre Hospital, University of CopenhagenDepartment of Surgical Gastroenterology 360, Hvidovre Hospital, University of CopenhagenApplied Proteomics, IncApplied Proteomics, IncAbstract Background The aim was to improve upon an existing blood-based colorectal cancer (CRC) test directed to high-risk symptomatic patients, by developing a new CRC classifier to be used with a new test embodiment. The new test uses a robust assay format—electrochemiluminescence immunoassays—to quantify protein concentrations. The aim was achieved by building and validating a CRC classifier using concentration measures from a large sample set representing a true intent-to-test (ITT) symptomatic population. Methods 4435 patient samples were drawn from the Endoscopy II sample set. Samples were collected at seven hospitals across Denmark between 2010 and 2012 from subjects with symptoms of colorectal neoplasia. Colonoscopies revealed the presence or absence of CRC. 27 blood plasma proteins were selected as candidate biomarkers based on previous studies. Multiplexed electrochemiluminescence assays were used to measure the concentrations of these 27 proteins in all 4435 samples. 3066 patients were randomly assigned to the Discovery set, in which machine learning was used to build candidate classifiers. Some classifiers were refined by allowing up to a 25% indeterminate score range. The classifier with the best Discovery set performance was successfully validated in the separate Validation set, consisting of 1336 samples. Results The final classifier was a logistic regression using ten predictors: eight proteins (A1AG, CEA, CO9, DPPIV, MIF, PKM2, SAA, TFRC), age, and gender. In validation, the indeterminate rate of the new panel was 23.2%, sensitivity/specificity was 0.80/0.83, PPV was 36.5%, and NPV was 97.1%. Conclusions The validated classifier serves as the basis of a new blood-based CRC test for symptomatic patients. The improved performance, resulting from robust concentration measures across a large sample set mirroring the ITT population, renders the new test the best available for this population. Results from a test using this classifier can help assess symptomatic patients’ CRC risk, increase their colonoscopy compliance, and manage next steps in their care.http://link.springer.com/article/10.1186/s12014-017-9163-zBlood testsClinical markersColorectal neoplasmsTumor biomarkersProteomics
collection DOAJ
language English
format Article
sources DOAJ
author Lisa J. Croner
Roslyn Dillon
Athit Kao
Stefanie N. Kairs
Ryan Benz
Ib J. Christensen
Hans J. Nielsen
John E. Blume
Bruce Wilcox
spellingShingle Lisa J. Croner
Roslyn Dillon
Athit Kao
Stefanie N. Kairs
Ryan Benz
Ib J. Christensen
Hans J. Nielsen
John E. Blume
Bruce Wilcox
Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects
Clinical Proteomics
Blood tests
Clinical markers
Colorectal neoplasms
Tumor biomarkers
Proteomics
author_facet Lisa J. Croner
Roslyn Dillon
Athit Kao
Stefanie N. Kairs
Ryan Benz
Ib J. Christensen
Hans J. Nielsen
John E. Blume
Bruce Wilcox
author_sort Lisa J. Croner
title Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects
title_short Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects
title_full Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects
title_fullStr Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects
title_full_unstemmed Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects
title_sort discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects
publisher BMC
series Clinical Proteomics
issn 1542-6416
1559-0275
publishDate 2017-07-01
description Abstract Background The aim was to improve upon an existing blood-based colorectal cancer (CRC) test directed to high-risk symptomatic patients, by developing a new CRC classifier to be used with a new test embodiment. The new test uses a robust assay format—electrochemiluminescence immunoassays—to quantify protein concentrations. The aim was achieved by building and validating a CRC classifier using concentration measures from a large sample set representing a true intent-to-test (ITT) symptomatic population. Methods 4435 patient samples were drawn from the Endoscopy II sample set. Samples were collected at seven hospitals across Denmark between 2010 and 2012 from subjects with symptoms of colorectal neoplasia. Colonoscopies revealed the presence or absence of CRC. 27 blood plasma proteins were selected as candidate biomarkers based on previous studies. Multiplexed electrochemiluminescence assays were used to measure the concentrations of these 27 proteins in all 4435 samples. 3066 patients were randomly assigned to the Discovery set, in which machine learning was used to build candidate classifiers. Some classifiers were refined by allowing up to a 25% indeterminate score range. The classifier with the best Discovery set performance was successfully validated in the separate Validation set, consisting of 1336 samples. Results The final classifier was a logistic regression using ten predictors: eight proteins (A1AG, CEA, CO9, DPPIV, MIF, PKM2, SAA, TFRC), age, and gender. In validation, the indeterminate rate of the new panel was 23.2%, sensitivity/specificity was 0.80/0.83, PPV was 36.5%, and NPV was 97.1%. Conclusions The validated classifier serves as the basis of a new blood-based CRC test for symptomatic patients. The improved performance, resulting from robust concentration measures across a large sample set mirroring the ITT population, renders the new test the best available for this population. Results from a test using this classifier can help assess symptomatic patients’ CRC risk, increase their colonoscopy compliance, and manage next steps in their care.
topic Blood tests
Clinical markers
Colorectal neoplasms
Tumor biomarkers
Proteomics
url http://link.springer.com/article/10.1186/s12014-017-9163-z
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