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Prediction and clinical utility of a contralateral breast cancer risk model.

Authors :
Giardiello D
Steyerberg EW
Hauptmann M
Adank MA
Akdeniz D
Blomqvist C
Bojesen SE
Bolla MK
Brinkhuis M
Chang-Claude J
Czene K
Devilee P
Dunning AM
Easton DF
Eccles DM
Fasching PA
Figueroa J
Flyger H
García-Closas M
Haeberle L
Haiman CA
Hall P
Hamann U
Hopper JL
Jager A
Jakubowska A
Jung A
Keeman R
Kramer I
Lambrechts D
Le Marchand L
Lindblom A
Lubiński J
Manoochehri M
Mariani L
Nevanlinna H
Oldenburg HSA
Pelders S
Pharoah PDP
Shah M
Siesling S
Smit VTHBM
Southey MC
Tapper WJ
Tollenaar RAEM
van den Broek AJ
van Deurzen CHM
van Leeuwen FE
van Ongeval C
Van't Veer LJ
Wang Q
Wendt C
Westenend PJ
Hooning MJ
Schmidt MK
Source :
Breast cancer research : BCR [Breast Cancer Res] 2019 Dec 17; Vol. 21 (1), pp. 144. Date of Electronic Publication: 2019 Dec 17.
Publication Year :
2019

Abstract

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.<br />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.<br />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.<br />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.

Details

Language :
English
ISSN :
1465-542X
Volume :
21
Issue :
1
Database :
MEDLINE
Journal :
Breast cancer research : BCR
Publication Type :
Academic Journal
Accession number :
31847907
Full Text :
https://doi.org/10.1186/s13058-019-1221-1