Gordon C. Wishart
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 D.P.
Authors
Professor EMAD RAKHA Emad.Rakha@nottingham.ac.uk
PROFESSOR OF BREAST CANCER PATHOLOGY
Dr Andy Green ANDREW.GREEN@NOTTINGHAM.AC.UK
ASSOCIATE PROFESSOR
Ian Ellis
Hamid Raza Ali
Elena Provenzano
Fiona M. Blows
Carlos Caldas
Paul D.P. Pharoah
Abstract
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.
Citation
Wishart, G. C., Rakha, E., Green, A., Ellis, I., Ali, H. R., Provenzano, E., Blows, F. M., Caldas, C., & Pharoah, P. D. (2014). Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer. BMC Cancer, 14(1), Article 908. https://doi.org/10.1186/1471-2407-14-908
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 20, 2014 |
Online Publication Date | Dec 3, 2014 |
Publication Date | 2014-12 |
Deposit Date | Oct 16, 2018 |
Publicly Available Date | Oct 17, 2018 |
Journal | BMC Cancer |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 14 |
Issue | 1 |
Article Number | 908 |
DOI | https://doi.org/10.1186/1471-2407-14-908 |
Public URL | https://nottingham-repository.worktribe.com/output/1169792 |
Publisher URL | https://bmccancer.biomedcentral.com/articles/10.1186/1471-2407-14-908 |
Contract Date | Oct 16, 2018 |
Files
1471-2407-14-908
(329 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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