학술논문

PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients
Document Type
article
Source
Breast Cancer Research. 24(1)
Subject
Genetics
Breast Cancer
Prevention
Cancer
Humans
Female
Breast Neoplasms
Mastectomy
Prophylactic Mastectomy
Germ-Line Mutation
Risk Factors
Contralateral breast cancer
Risk prediction
Contralateral preventive mastectomy
Clinical decision-making
Breast cancer genetic predisposition
Breast Cancer Association Consortium
BCAC
Prediction performance
BRCA1/2 germline mutation
Polygenic risk score
Oncology and Carcinogenesis
Oncology & Carcinogenesis
Language
Abstract
BackgroundPrediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors.MethodsWe included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models.ResultsThe discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56-0.74) versus 0.63 (95%PI 0.54-0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34-2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.ConclusionsAdditional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.