Abstract
Purpose
Black breast cancer (BC) survivors have a higher risk of developing contralateral breast cancer (CBC) than Whites. Existing CBC risk prediction tools are developed based on mostly White women. To address this racial disparity, it is crucial to develop tools tailored for Black women to help them inform about their actual risk of CBC.
Methods
We propose an absolute risk prediction model, CBCRisk-Black, specifically for Black BC patients. It uses data on Black women from two sources: Breast Cancer Surveillance Consortium (BCSC) and Surveillance, Epidemiology, and End Results (SEER). First, a matched lasso logistic regression model for estimating relative risks (RR) is developed. Then, it is combined with relevant hazard rates and attributable risks to obtain absolute risks. Six-fold cross-validation is used to internally validate CBCRisk-Black. We also compare CBCRisk-Black with CBCRisk, an existing CBC risk prediction model.
Results
The RR model uses data from BCSC on 744 Black women (186 cases). CBCRisk-Black has four risk factors (RR compared to baseline): breast density (2.13 for heterogeneous/extremely dense), family history of BC (2.28 for yes), first BC tumor size (2.14 for T3/T4, 1.56 for TIS), and age at first diagnosis of BC (1.41 for < 40). The area under the receiver operating characteristic curve (AUC) for 3- and 5-year predictions are 0.72 and 0.65 for CBCRisk-Black while those are 0.65 and 0.60 for CBCRisk.
Conclusion
CBCRisk-Black may serve as a useful tool to clinicians in counseling Black BC patients by providing a more accurate and personalized CBC risk estimate.
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BCSC data can be requested at https://www.bcsc-research.org/. SEER data can be requested at https://seer.cancer.gov/.
Code availability
Software implementing CBCRisk-Black will be available at https://personal.utdallas.edu/~swati.biswas/.
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Acknowledgements
Data collection was supported in part by the National Cancer Institute-funded Breast Cancer Surveillance Consortium (HHSN261201100031C and P01CA154292). The collection of BCSC cancer and vital status data was supported in part by several state public health departments and cancer registries throughout the U.S. (http://www.bcsc-research.org/work/acknowledgement.html). All statements in this report, including its findings and conclusions, are solely those of the authors and do not necessarily represent the views of the National Cancer Institute or National Institutes of Health. We thank the participating women, mammography facilities, and radiologists for the data they have provided. You can learn more about the BCSC at: http://www.bcsc-research.org/. We thank the anonymous reviewers for their constructive comments and suggestions, which have led to an improved manuscript.
Funding
This project was partially funded by the National Cancer Institute at the National Institutes of Health (Grant Number R21 CA186086).
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Sajal, I.H., Chowdhury, M., Wang, T. et al. CBCRisk-Black: a personalized contralateral breast cancer risk prediction model for black women. Breast Cancer Res Treat 194, 179–186 (2022). https://doi.org/10.1007/s10549-022-06612-5
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DOI: https://doi.org/10.1007/s10549-022-06612-5