Risk assessment and prognosis of breast cancer
Description: Today, one in eight women develops breast cancer during her lifetime. Mammography screening reduces breast cancer mortality by 20-40% but is suboptimal for tumors not detected in screening. The addition of personalized risk assessment to standard of care could improve the early detection of women who currently do not benefit from screening. In addition, women who develop breast cancer have a survival of 30-99% depending on tumor characteristics and treatment options. A mammography surveillance tool is needed that takes into account for patient and tumor characteristics to enable earlier detection of a recurring cancer.In a collaboration between Karolinska Institutet, Cambridge University, and European and US. clinics we propose a 3-year project to develop an AI-based risk model based on mammographic features, lifestyle factors, and genetic determinants to identify women at high risk of aggressive breast cancer in the general population. Further, we propose to develop an AI algorithm for surveillance of women who are at risk of recurrence. In a genome-wide association study we also investigate the genetic determinants of the novel mammographic features identified in this project. The project is based on a multi-ethnic study population.The proposed project could form clinical strategies to improve breast cancer survival for women who currently do not benefit from mammography screening and, for women who need improved surveillance due to their high risk of a recurring tumor.
Funder: Vetenskapsrådet
Amount: SEK 3,450,000
Funding type: fellowship
Funder scheme: Grant for positions or stipends
Start date: 2023-01-01
End date: 2025-12-31
Investigator: Mikael Eriksson
Institution: Karolinska Institutet
Funded outputs count: 1
Funder award ID: 2022-06148
OpenAlex ID: G8581786141