Prediction and clinical utility of a contralateral breast cancer risk model.
Creators: name: Giardiello, Daniele
name: Steyerberg, Ewout W
name: Hauptmann, Michael
name: Adank, Muriel A
name: Akdeniz, Delal
name: Blomqvist, Carl
name: Bojesen, Stig E
name: Bolla, Manjeet K
name: Brinkhuis, Mariël
name: Chang-Claude, Jenny
name: Czene, Kamila
name: Devilee, Peter
name: Dunning, Alison M
name: Easton, Douglas F
name: Eccles, Diana M
name: Fasching, Peter A
name: Figueroa, Jonine
name: Flyger, Henrik
name: García-Closas, Montserrat
name: Haeberle, Lothar
name: Haiman, Christopher A
name: Hall, Per
name: Hamann, Ute
name: Hopper, John L
name: Jager, Agnes
name: Jakubowska, Anna
name: Jung, Audrey
name: Keeman, Renske
name: Kramer, Iris
name: Lambrechts, Diether
name: Le Marchand, Loic
name: Lindblom, Annika
name: Lubiński, Jan
name: Manoochehri, Mehdi
name: Mariani, Luigi
name: Nevanlinna, Heli
name: Oldenburg, Hester S A
name: Pelders, Saskia
name: Pharoah, Paul D P
name: Shah, Mitul
name: Siesling, Sabine
name: Smit, Vincent T H B M
name: Southey, Melissa C
name: Tapper, William J
name: Tollenaar, Rob A E M
name: Van Den Broek, Alexandra J
name: Van Deurzen, Carolien H M
name: Van Leeuwen, Flora E
name: Van Ongeval, Chantal
name: Van't Veer, Laura J
name: Wang, Qin
name: Wendt, Camilla
name: Westenend, Pieter J
name: Hooning, Maartje J
name: Schmidt, Marjanka K
Publisher: name: Apollo - University of Cambridge Repository
Year: 2019
Subjects: Clinical Decision-making
Contralateral Breast Cancer
Risk Prediction Model
Brca Mutation Carriers

description: BACKGROUND:Breast cancer survivors are at risk for contralateral breast cancer (CBC), with the consequent burden of further treatment and potentially less favorable prognosis. We aimed to develop and validate a CBC risk prediction model and evaluate its applicability for clinical decision-making. METHODS:We included data of 132,756 invasive non-metastatic breast cancer patients from 20 studies with 4682 CBC events and a median follow-up of 8.8 years. We developed a multivariable Fine and Gray prediction model (PredictCBC-1A) including patient, primary tumor, and treatment characteristics and BRCA1/2 germline mutation status, accounting for the competing risks of death and distant metastasis. We also developed a model without BRCA1/2 mutation status (PredictCBC-1B) since this information was available for only 6% of patients and is routinely unavailable in the general breast cancer population. Prediction performance was evaluated using calibration and discrimination, calculated by a time-dependent area under the curve (AUC) at 5 and 10 years after diagnosis of primary breast cancer, and an internal-external cross-validation procedure. Decision curve analysis was performed to evaluate the net benefit of the model to quantify clinical utility. RESULTS:In the multivariable model, BRCA1/2 germline mutation status, family history, and systemic adjuvant treatment showed the strongest associations with CBC risk. The AUC of PredictCBC-1A was 0.63 (95% prediction interval (PI) at 5 years, 0.52-0.74; at 10 years, 0.53-0.72). Calibration-in-the-large was -0.13 (95% PI: -1.62-1.37), and the calibration slope was 0.90 (95% PI: 0.73-1.08). The AUC of Predict-1B at 10 years was 0.59 (95% PI: 0.52-0.66); calibration was slightly lower. Decision curve analysis for preventive contralateral mastectomy showed potential clinical utility of PredictCBC-1A between thresholds of 4-10% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers. CONCLUSIONS:We developed a reasonably calibrated model to predict the risk of CBC in women of European-descent; however, prediction accuracy was moderate. Our model shows potential for improved risk counseling, but decision-making regarding contralateral preventive mastectomy, especially in the general breast cancer population where limited information of the mutation status in BRCA1/2 is available, remains challenging.