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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

Gordon C. Wishart

EMAD RAKHA Emad.Rakha@nottingham.ac.uk
Professor of Breast Cancer Pathology

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., …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 Mar 28, 2024
Journal BMC Cancer
Publisher BMC
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