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Development and Preliminary Evaluation of a Multivariate Index Assay for Ovarian Cancer
BACKGROUND: Most women with a clinical presentation consistent with ovarian cancer have benign conditions. Therefore methods to distinguish women with ovarian cancer from those with benign conditions would be beneficial. We describe the development and preliminary evaluation of a serum-based multiva...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2643010/ https://www.ncbi.nlm.nih.gov/pubmed/19240799 http://dx.doi.org/10.1371/journal.pone.0004599 |
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author | Amonkar, Suraj D. Bertenshaw, Greg P. Chen, Tzong-Hao Bergstrom, Katharine J. Zhao, Jinghua Seshaiah, Partha Yip, Ping Mansfield, Brian C. |
author_facet | Amonkar, Suraj D. Bertenshaw, Greg P. Chen, Tzong-Hao Bergstrom, Katharine J. Zhao, Jinghua Seshaiah, Partha Yip, Ping Mansfield, Brian C. |
author_sort | Amonkar, Suraj D. |
collection | PubMed |
description | BACKGROUND: Most women with a clinical presentation consistent with ovarian cancer have benign conditions. Therefore methods to distinguish women with ovarian cancer from those with benign conditions would be beneficial. We describe the development and preliminary evaluation of a serum-based multivariate assay for ovarian cancer. This hypothesis-driven study examined whether an informative pattern could be detected in stage I disease that persists through later stages. METHODOLOGY/PRINCIPAL FINDINGS: Sera, collected under uniform protocols from multiple institutions, representing 176 cases and 187 controls from women presenting for surgery were examined using high-throughput, multiplexed immunoassays. All stages and common subtypes of epithelial ovarian cancer, and the most common benign ovarian conditions were represented. A panel of 104 antigens, 44 autoimmune and 56 infectious disease markers were assayed and informative combinations identified. Using a training set of 91 stage I data sets, representing 61 individual samples, and an equivalent number of controls, an 11-analyte profile, composed of CA-125, CA 19-9, EGF-R, C-reactive protein, myoglobin, apolipoprotein A1, apolipoprotein CIII, MIP-1α, IL-6, IL-18 and tenascin C was identified and appears informative for all stages and common subtypes of ovarian cancer. Using a testing set of 245 samples, approximately twice the size of the model building set, the classifier had 91.3% sensitivity and 88.5% specificity. While these preliminary results are promising, further refinement and extensive validation of the classifier in a clinical trial is necessary to determine if the test has clinical value. CONCLUSIONS/SIGNIFICANCE: We describe a blood-based assay using 11 analytes that can distinguish women with ovarian cancer from those with benign conditions. Preliminary evaluation of the classifier suggests it has the potential to offer approximately 90% sensitivity and 90% specificity. While promising, the performance needs to be assessed in a blinded clinical validation study. |
format | Text |
id | pubmed-2643010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-26430102009-02-25 Development and Preliminary Evaluation of a Multivariate Index Assay for Ovarian Cancer Amonkar, Suraj D. Bertenshaw, Greg P. Chen, Tzong-Hao Bergstrom, Katharine J. Zhao, Jinghua Seshaiah, Partha Yip, Ping Mansfield, Brian C. PLoS One Research Article BACKGROUND: Most women with a clinical presentation consistent with ovarian cancer have benign conditions. Therefore methods to distinguish women with ovarian cancer from those with benign conditions would be beneficial. We describe the development and preliminary evaluation of a serum-based multivariate assay for ovarian cancer. This hypothesis-driven study examined whether an informative pattern could be detected in stage I disease that persists through later stages. METHODOLOGY/PRINCIPAL FINDINGS: Sera, collected under uniform protocols from multiple institutions, representing 176 cases and 187 controls from women presenting for surgery were examined using high-throughput, multiplexed immunoassays. All stages and common subtypes of epithelial ovarian cancer, and the most common benign ovarian conditions were represented. A panel of 104 antigens, 44 autoimmune and 56 infectious disease markers were assayed and informative combinations identified. Using a training set of 91 stage I data sets, representing 61 individual samples, and an equivalent number of controls, an 11-analyte profile, composed of CA-125, CA 19-9, EGF-R, C-reactive protein, myoglobin, apolipoprotein A1, apolipoprotein CIII, MIP-1α, IL-6, IL-18 and tenascin C was identified and appears informative for all stages and common subtypes of ovarian cancer. Using a testing set of 245 samples, approximately twice the size of the model building set, the classifier had 91.3% sensitivity and 88.5% specificity. While these preliminary results are promising, further refinement and extensive validation of the classifier in a clinical trial is necessary to determine if the test has clinical value. CONCLUSIONS/SIGNIFICANCE: We describe a blood-based assay using 11 analytes that can distinguish women with ovarian cancer from those with benign conditions. Preliminary evaluation of the classifier suggests it has the potential to offer approximately 90% sensitivity and 90% specificity. While promising, the performance needs to be assessed in a blinded clinical validation study. Public Library of Science 2009-02-25 /pmc/articles/PMC2643010/ /pubmed/19240799 http://dx.doi.org/10.1371/journal.pone.0004599 Text en Amonkar et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Amonkar, Suraj D. Bertenshaw, Greg P. Chen, Tzong-Hao Bergstrom, Katharine J. Zhao, Jinghua Seshaiah, Partha Yip, Ping Mansfield, Brian C. Development and Preliminary Evaluation of a Multivariate Index Assay for Ovarian Cancer |
title | Development and Preliminary Evaluation of a Multivariate Index Assay for Ovarian Cancer |
title_full | Development and Preliminary Evaluation of a Multivariate Index Assay for Ovarian Cancer |
title_fullStr | Development and Preliminary Evaluation of a Multivariate Index Assay for Ovarian Cancer |
title_full_unstemmed | Development and Preliminary Evaluation of a Multivariate Index Assay for Ovarian Cancer |
title_short | Development and Preliminary Evaluation of a Multivariate Index Assay for Ovarian Cancer |
title_sort | development and preliminary evaluation of a multivariate index assay for ovarian cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2643010/ https://www.ncbi.nlm.nih.gov/pubmed/19240799 http://dx.doi.org/10.1371/journal.pone.0004599 |
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