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Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data
PURPOSE: Oncotype DX (ODX) recurrence score (RS) breast cancer (BC) assay is costly, and performed in only ~1/3 of estrogen receptor (ER)-positive BC patients in the USA. We have now developed a user-friendly nomogram surrogate prediction model for ODX based on a large dataset from the National Canc...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5387031/ https://www.ncbi.nlm.nih.gov/pubmed/28243897 http://dx.doi.org/10.1007/s10549-017-4170-3 |
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author | Orucevic, Amila Bell, John L. McNabb, Alison P. Heidel, Robert E. |
author_facet | Orucevic, Amila Bell, John L. McNabb, Alison P. Heidel, Robert E. |
author_sort | Orucevic, Amila |
collection | PubMed |
description | PURPOSE: Oncotype DX (ODX) recurrence score (RS) breast cancer (BC) assay is costly, and performed in only ~1/3 of estrogen receptor (ER)-positive BC patients in the USA. We have now developed a user-friendly nomogram surrogate prediction model for ODX based on a large dataset from the National Cancer Data Base (NCDB) to assist in selecting patients for which further ODX testing may not be necessary and as a surrogate for patients for which ODX testing is not affordable or available. METHODS: Six clinicopathologic variables of 27,719 ODX-tested ER+/HER2−/lymph node-negative patients with 6–50 mm tumor size captured by the NCDB from 2010 to 2012 were assessed with logistic regression to predict high-risk or low-risk ODXRS test results with TAILORx-trial and commercial cut-off values; 12,763 ODX-tested patients in 2013 were used for external validation. The predictive accuracy of the regression model was yielded using a Receiver Operator Characteristic analysis. Model fit was analyzed by plotting the predicted probabilities against the actual probabilities. A user-friendly calculator version of nomograms is available online at the University of Tennessee Medical Center website (Knoxville, TN). RESULTS: Grade and progesterone receptor status were the highest predictors of both low-risk and high-risk ODXRS, followed by age, tumor size, histologic tumor type and lymph-vascular invasion (C-indexes-.0.85 vs. 0.88 for TAILORx-trial vs. commercial cut-off values, respectively). CONCLUSION: This is the first study of this scale showing confidently that clinicopathologic variables can be used for prediction of low-risk or high-risk ODXRS using our nomogram models. These novel nomograms will be useful tools to help physicians and patients decide whether further ODX testing is necessary and are excellent surrogates for patients for which ODX testing is not affordable or available. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-017-4170-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5387031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-53870312017-04-27 Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data Orucevic, Amila Bell, John L. McNabb, Alison P. Heidel, Robert E. Breast Cancer Res Treat Preclinical Study PURPOSE: Oncotype DX (ODX) recurrence score (RS) breast cancer (BC) assay is costly, and performed in only ~1/3 of estrogen receptor (ER)-positive BC patients in the USA. We have now developed a user-friendly nomogram surrogate prediction model for ODX based on a large dataset from the National Cancer Data Base (NCDB) to assist in selecting patients for which further ODX testing may not be necessary and as a surrogate for patients for which ODX testing is not affordable or available. METHODS: Six clinicopathologic variables of 27,719 ODX-tested ER+/HER2−/lymph node-negative patients with 6–50 mm tumor size captured by the NCDB from 2010 to 2012 were assessed with logistic regression to predict high-risk or low-risk ODXRS test results with TAILORx-trial and commercial cut-off values; 12,763 ODX-tested patients in 2013 were used for external validation. The predictive accuracy of the regression model was yielded using a Receiver Operator Characteristic analysis. Model fit was analyzed by plotting the predicted probabilities against the actual probabilities. A user-friendly calculator version of nomograms is available online at the University of Tennessee Medical Center website (Knoxville, TN). RESULTS: Grade and progesterone receptor status were the highest predictors of both low-risk and high-risk ODXRS, followed by age, tumor size, histologic tumor type and lymph-vascular invasion (C-indexes-.0.85 vs. 0.88 for TAILORx-trial vs. commercial cut-off values, respectively). CONCLUSION: This is the first study of this scale showing confidently that clinicopathologic variables can be used for prediction of low-risk or high-risk ODXRS using our nomogram models. These novel nomograms will be useful tools to help physicians and patients decide whether further ODX testing is necessary and are excellent surrogates for patients for which ODX testing is not affordable or available. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-017-4170-3) contains supplementary material, which is available to authorized users. Springer US 2017-02-27 2017 /pmc/articles/PMC5387031/ /pubmed/28243897 http://dx.doi.org/10.1007/s10549-017-4170-3 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Preclinical Study Orucevic, Amila Bell, John L. McNabb, Alison P. Heidel, Robert E. Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data |
title | Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data |
title_full | Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data |
title_fullStr | Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data |
title_full_unstemmed | Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data |
title_short | Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data |
title_sort | oncotype dx breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data |
topic | Preclinical Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5387031/ https://www.ncbi.nlm.nih.gov/pubmed/28243897 http://dx.doi.org/10.1007/s10549-017-4170-3 |
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