PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients.
Creators: name: Giardiello, Daniele
name: Hooning, Maartje J
name: Hauptmann, Michael
name: Keeman, Renske
name: Heemskerk-Gerritsen, B A M
name: Becher, Heiko
name: Blomqvist, Carl
name: Bojesen, Stig E
name: Bolla, Manjeet K
name: Camp, Nicola J
name: Czene, Kamila
name: Devilee, Peter
name: Eccles, Diana M
name: Fasching, Peter A
name: Figueroa, Jonine D
name: Flyger, Henrik
name: García-Closas, Montserrat
name: Haiman, Christopher A
name: Hamann, Ute
name: Hopper, John L
name: Jakubowska, Anna
name: Leeuwen, Floor E
name: Lindblom, Annika
name: Lubiński, Jan
name: Margolin, Sara
name: Martinez, Maria Elena
name: Nevanlinna, Heli
name: Nevelsteen, Ines
name: Pelders, Saskia
name: Pharoah, Paul D P
name: Siesling, Sabine
name: Southey, Melissa C
name: Van Der Hout, Annemieke H
name: Van Hest, Liselotte P
name: Chang-Claude, Jenny
name: Hall, Per
name: Easton, Douglas F
name: Steyerberg, Ewout W
name: Schmidt, Marjanka K
Publisher: name: Apollo - University of Cambridge Repository
Year: 2022
Subjects: Clinical Decision-making
Risk Prediction
Contralateral Breast Cancer
Polygenic Risk Score
Prediction Performance
Bcac
Breast Cancer Association Consortium
Brca1/2 Germline Mutation
Contralateral Preventive Mastectomy
Breast Cancer Genetic Predisposition
Humans
Breast Neoplasms
Mastectomy
Risk Factors
Germ-Line Mutation
Female
Prophylactic Mastectomy

description: 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.