Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Breast Cancer Res Treat. 2020 Jun;181(2):423-434. doi: 10.1007/s10549-020-05611-8. Epub 2020 Apr 11.
Three tools are currently available to predict the risk of contralateral breast cancer (CBC). We aimed to compare the performance of the Manchester formula, CBCrisk, and PredictCBC in patients with invasive breast cancer (BC).
We analyzed data of 132,756 patients (4682 CBC) from 20 international studies with a median follow-up of 8.8 years. Prediction performance included discrimination, quantified as a time-dependent Area-Under-the-Curve (AUC) at 5 and 10 years after diagnosis of primary BC, and calibration, quantified as the expected-observed (E/O) ratio at 5 and 10 years and the calibration slope.
The AUC at 10 years was: 0.58 (95% confidence intervals [CI] 0.57-0.59) for CBCrisk; 0.60 (95% CI 0.59-0.61) for the Manchester formula; 0.63 (95% CI 0.59-0.66) and 0.59 (95% CI 0.56-0.62) for PredictCBC-1A (for settings where BRCA1/2 mutation status is available) and PredictCBC-1B (for the general population), respectively. The E/O at 10 years: 0.82 (95% CI 0.51-1.32) for CBCrisk; 1.53 (95% CI 0.63-3.73) for the Manchester formula; 1.28 (95% CI 0.63-2.58) for PredictCBC-1A and 1.35 (95% CI 0.65-2.77) for PredictCBC-1B. The calibration slope was 1.26 (95% CI 1.01-1.50) for CBCrisk; 0.90 (95% CI 0.79-1.02) for PredictCBC-1A; 0.81 (95% CI 0.63-0.99) for PredictCBC-1B, and 0.39 (95% CI 0.34-0.43) for the Manchester formula.
Current CBC risk prediction tools provide only moderate discrimination and the Manchester formula was poorly calibrated. Better predictors and re-calibration are needed to improve CBC prediction and to identify low- and high-CBC risk patients for clinical decision-making.
目前有三种工具可用于预测对侧乳腺癌（CBC）的风险。我们旨在比较曼彻斯特公式、CBCrisk 和 PredictCBC 在浸润性乳腺癌（BC）患者中的表现。
我们分析了来自 20 项国际研究的 132756 名患者（4682 例 CBC）的数据，中位随访时间为 8.8 年。预测性能包括区分度，以诊断原发性 BC 后 5 年和 10 年的时间依赖性曲线下面积（AUC）来量化；校准度，以诊断原发性 BC 后 5 年和 10 年的预期-观察比（E/O）和校准斜率来量化。
10 年时的 AUC 为：CBCrisk 为 0.58（95%置信区间 [CI] 0.57-0.59）；曼彻斯特公式为 0.60（95%CI 0.59-0.61）；PredictCBC-1A（BRCA1/2 基因突变状态可用时）为 0.63（95%CI 0.59-0.66），PredictCBC-1B（一般人群）为 0.59（95%CI 0.56-0.62）。10 年时的 E/O 为：CBCrisk 为 0.82（95%CI 0.51-1.32）；曼彻斯特公式为 1.53（95%CI 0.63-3.73）；PredictCBC-1A 为 1.28（95%CI 0.63-2.58），PredictCBC-1B 为 1.35（95%CI 0.65-2.77）。CBCrisk 的校准斜率为 1.26（95%CI 1.01-1.50）；PredictCBC-1A 为 0.90（95%CI 0.79-1.02）；PredictCBC-1B 为 0.81（95%CI 0.63-0.99）；曼彻斯特公式为 0.39（95%CI 0.34-0.43）。
目前的 CBC 风险预测工具仅提供中等程度的区分度，曼彻斯特公式的校准效果较差。需要更好的预测器和重新校准来提高 CBC 预测，并为临床决策确定低风险和高风险的 CBC 患者。
