PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients.

ABSTRACT:

Background

Prediction 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.

Methods

We 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

SUBMITTER: Giardiello D 

PROVIDER: S-EPMC9585761 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature