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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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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