CBCRisk-Mastectomy: A Prediction Tool to Aid Contralateral Prophylactic Mastectomy Decision-Making

Area of Science:

• Oncology
• Biostatistics
• Epidemiology

Background:

• Unilateral breast cancer (BC) patients often opt for contralateral prophylactic mastectomy (CPM) despite decreasing contralateral breast cancer (CBC) risk.
• Risk prediction models can support informed decisions regarding CPM.

Purpose of the Study:

• To develop and validate CBCRisk-Mastectomy, a risk prediction model specifically for BC patients undergoing mastectomy.
• To improve decision-making for CPM in BC patients.

Main Methods:

• Utilized data from the Breast Cancer Surveillance Consortium (BCSC) and SEER cancer registry.
• Employed conditional logistic regression models trained on 2660 BC patients (665 CBC cases) from BCSC.
• Integrated SEER data for absolute risk estimation and cross-validation for internal validation and comparison with CBCRisk.

Main Results:

• CBCRisk-Mastectomy incorporates nine predictors: first BC type, lobular carcinoma in situ status, estrogen receptor status, tumor stage, breast density, age at BC diagnosis, family history of BC, age at first birth, and body mass index.
• Achieved a higher area under the curve (0.62) for five-year CBC risk prediction compared to the existing CBCRisk model (0.58).

Conclusions:

• CBCRisk-Mastectomy offers a valuable tool for clinicians counseling BC patients scheduled for mastectomy.
• The model can enhance informed decision-making regarding CPM by providing personalized risk assessments.