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Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer
BACKGROUND: PREDICT (http://www.predict.nhs.uk) is a prognostication and treatment benefit tool for early breast cancer (EBC). The aim of this study was to incorporate the prognostic effect of KI67 status in a new version (v3), and compare performance with the Predict model that includes HER2 status...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4265394/ https://www.ncbi.nlm.nih.gov/pubmed/25472026 http://dx.doi.org/10.1186/1471-2407-14-908 |
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author | Wishart, Gordon C Rakha, Emad Green, Andrew Ellis, Ian Ali, Hamid Raza Provenzano, Elena Blows, Fiona M Caldas, Carlos Pharoah, Paul DP |
author_facet | Wishart, Gordon C Rakha, Emad Green, Andrew Ellis, Ian Ali, Hamid Raza Provenzano, Elena Blows, Fiona M Caldas, Carlos Pharoah, Paul DP |
author_sort | Wishart, Gordon C |
collection | PubMed |
description | BACKGROUND: PREDICT (http://www.predict.nhs.uk) is a prognostication and treatment benefit tool for early breast cancer (EBC). The aim of this study was to incorporate the prognostic effect of KI67 status in a new version (v3), and compare performance with the Predict model that includes HER2 status (v2). METHODS: The validation study was based on 1,726 patients with EBC treated in Nottingham between 1989 and 1998. KI67 positivity for PREDICT is defined as >10% of tumour cells staining positive. ROC curves were constructed for Predict models with (v3) and without (v2) KI67 input. Comparison was made using the method of DeLong. RESULTS: In 1274 ER+ patients the predicted number of events at 10 years increased from 196 for v2 to 204 for v3 compared to 221 observed. The area under the ROC curve (AUC) improved from 0.7611 to 0.7676 (p = 0.005) in ER+ patients and from 0.7546 to 0.7595 (p = 0.0008) in all 1726 patients (ER+ and ER-). CONCLUSION: Addition of KI67 to PREDICT has led to a statistically significant improvement in the model performance for ER+ patients and will aid clinical decision making in these patients. Further studies should determine whether other markers including gene expression profiling provide additional prognostic information to that provided by PREDICT. |
format | Online Article Text |
id | pubmed-4265394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42653942014-12-15 Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer Wishart, Gordon C Rakha, Emad Green, Andrew Ellis, Ian Ali, Hamid Raza Provenzano, Elena Blows, Fiona M Caldas, Carlos Pharoah, Paul DP BMC Cancer Research Article BACKGROUND: PREDICT (http://www.predict.nhs.uk) is a prognostication and treatment benefit tool for early breast cancer (EBC). The aim of this study was to incorporate the prognostic effect of KI67 status in a new version (v3), and compare performance with the Predict model that includes HER2 status (v2). METHODS: The validation study was based on 1,726 patients with EBC treated in Nottingham between 1989 and 1998. KI67 positivity for PREDICT is defined as >10% of tumour cells staining positive. ROC curves were constructed for Predict models with (v3) and without (v2) KI67 input. Comparison was made using the method of DeLong. RESULTS: In 1274 ER+ patients the predicted number of events at 10 years increased from 196 for v2 to 204 for v3 compared to 221 observed. The area under the ROC curve (AUC) improved from 0.7611 to 0.7676 (p = 0.005) in ER+ patients and from 0.7546 to 0.7595 (p = 0.0008) in all 1726 patients (ER+ and ER-). CONCLUSION: Addition of KI67 to PREDICT has led to a statistically significant improvement in the model performance for ER+ patients and will aid clinical decision making in these patients. Further studies should determine whether other markers including gene expression profiling provide additional prognostic information to that provided by PREDICT. BioMed Central 2014-12-03 /pmc/articles/PMC4265394/ /pubmed/25472026 http://dx.doi.org/10.1186/1471-2407-14-908 Text en © Wishart et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Wishart, Gordon C Rakha, Emad Green, Andrew Ellis, Ian Ali, Hamid Raza Provenzano, Elena Blows, Fiona M Caldas, Carlos Pharoah, Paul DP Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer |
title | Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer |
title_full | Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer |
title_fullStr | Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer |
title_full_unstemmed | Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer |
title_short | Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer |
title_sort | inclusion of ki67 significantly improves performance of the predict prognostication and prediction model for early breast cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4265394/ https://www.ncbi.nlm.nih.gov/pubmed/25472026 http://dx.doi.org/10.1186/1471-2407-14-908 |
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