Prediction and clinical utility of a contralateral breast cancer risk model.
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... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2019 |
Verlag/Hrsg.: |
Springer Science and Business Media LLC
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Schlagwörter: | BRCA mutation carriers / Clinical decision-making / Contralateral breast cancer / Risk prediction model / Area Under Curve / BRCA1 Protein / BRCA2 Protein / Breast Neoplasms / Disease Management / Disease Susceptibility / Female / Germ-Line Mutation / Humans / Neoplasms / Second Primary / Netherlands / Prognosis / Proportional Hazards Models / Risk Assessment / Risk Factors |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-28782282 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://www.repository.cam.ac.uk/handle/1810/301058 |
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 ...