TY - JOUR

T1 - Prediction and clinical utility of a contralateral breast cancer risk model

AU - Giardiello, Daniele

AU - Steyerberg, Ewout W.

AU - Hauptmann, Michael

AU - Adank, Muriel A.

AU - Akdeniz, Delal

AU - Blomqvist, Carl

AU - Bojesen, Stig E.

AU - Bolla, Manjeet K.

AU - Brinkhuis, Mariël

AU - Chang-Claude, Jenny

AU - Czene, Kamila

AU - Devilee, Peter

AU - Dunning, Alison M.

AU - Easton, Douglas F.

AU - Eccles, Diana M.

AU - Fasching, Peter A.

AU - Figueroa, Jonine

AU - Flyger, Henrik

AU - Garciá-Closas, Montserrat

AU - Haeberle, Lothar

AU - Haiman, Christopher A.

AU - Hall, Per

AU - Hamann, Ute

AU - Hopper, John L.

AU - Jager, Agnes

AU - Jakubowska, Anna

AU - Jung, Audrey

AU - Keeman, Renske

AU - Kramer, Iris

AU - Lambrechts, Diether

AU - Le Marchand, Loic

AU - Lindblom, Annika

AU - Lubiński, Jan

AU - Manoochehri, Mehdi

AU - Mariani, Luigi

AU - Nevanlinna, Heli

AU - Oldenburg, Hester S.A.

AU - Pelders, Saskia

AU - Pharoah, Paul D.P.

AU - Shah, Mitul

AU - Siesling, Sabine

AU - Smit, Vincent T.H.B.M.

AU - Southey, Melissa C.

AU - Tapper, William J.

AU - Tollenaar, Rob A.E.M.

AU - Van Den Broek, Alexandra J.

AU - Van Deurzen, Carolien H.M.

AU - Van Leeuwen, Flora E.

AU - Van Ongeval, Chantal

AU - Van't Veer, Laura J.

AU - Wang, Qin

AU - Wendt, Camilla

AU - Westenend, Pieter J.

AU - Hooning, Maartje J.

AU - Schmidt, Marjanka K.

PY - 2019/12

Y1 - 2019/12

N2 - 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.

AB - 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.

KW - BRCA mutation carriers

KW - Clinical decision-making

KW - Contralateral breast cancer

KW - Risk prediction model

U2 - 10.1186/s13058-019-1221-1

DO - 10.1186/s13058-019-1221-1

M3 - Journal article

C2 - 31847907

AN - SCOPUS:85076826918

VL - 21

JO - Breast Cancer Research

JF - Breast Cancer Research

SN - 1465-5411

M1 - 144

ER -