Good risk prediction models can be used in clinic to predict the individual risk of developing breast cancer. Most current models for breast cancer include lifestyle factors and family history of breast cancer. Some include mammographic density or genetic determinants.
We have developed a new model for individualised short-term risk prediction, called CAD2Y. The prediction model has been developed using mammographic density, computer-aided detection of microcalcifications and masses, use of menopausal hormone therapy, family history of breast cancer, menopausal status, age, and body mass index.
Applying CAD2Y to the Karma population enabled early identification of women within the mammography-screening program at such high risk of breast cancer that additional examinations are warranted. In contrast, women at low risk could probably be screened less intensively.
We are currently working on adding more risk factors to the model to further improve the predictive power.
The CAD2Y risk model is developed in collaboration with iCAD [icadmed.com].
For a detailed description of the CAD2Y breast cancer risk prediction model, please see [Eriksson, 2017].
Eriksson M, Czene K, Pawitan Y, Leifland K, Darabi H, Hall P. A clinical model for identifying the short-term risk of breast cancer. Breast Cancer Res. 2017 Mar 14;19(1):29. doi: 10.1186/s13058-017-0820-y.PMID: 28288659