Abstract P5-07-12: Prediction and clinical utility of a contralateral breast cancer risk model

Abstract

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. Methods: We included data of 132,756 invasive non-metastatic breast cancer patients from 20 studies with 4,682 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). 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 regarding contralateral preventive mastectomy, especially in the general breast cancer population, remains challenging. Citation Format: Daniele Giardiello, Ewout W Steyerberg, Michael Hauptmann, Muriel A Adank, Agnes Jager, Hester OA Oldenburg, Maartje J Hooning, Marjanka K Schmidt, Breast Cancer Association Consortium. Prediction and clinical utility of a contralateral breast cancer risk model [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-07-12.