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.

中文翻译：

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对侧乳腺癌风险模型的预测和临床实用性。


背景乳腺癌幸存者有患对侧乳腺癌（CBC）的风险，从而带来进一步治疗的负担和可能较差的预后。我们的目的是开发和验证 CBC 风险预测模型，并评估其对临床决策的适用性。方法 我们纳入了来自 20 项研究的 132,756 名侵袭性非转移性乳腺癌患者的数据，涉及 4682 次 CBC 事件，中位随访时间为 8.8 年。我们开发了多变量 Fine and Gray 预测模型 (PredictCBC-1A)，包括患者、原发肿瘤、治疗特征以及 BRCA1/2 种系突变状态，考虑了死亡和远处转移的竞争风险。我们还开发了一个没有 BRCA1/2 突变状态的模型 (PredictCBC-1B)，因为此信息仅适用于 6% 的患者，并且在一般乳腺癌人群中通常无法获得。使用校准和辨别来评估预测性能，通过原发性乳腺癌诊断后 5 年和 10 年的时间依赖性曲线下面积 (AUC) 计算，以及内部-外部交叉验证程序。进行决策曲线分析以评估模型的净效益以量化临床效用。结果在多变量模型中，BRCA1/2 种系突变状态、家族史和全身辅助治疗显示与 CBC 风险的关联最强。 PredictCBC-1A 的 AUC 为 0.63（5 年 95% 预测区间 (PI)，0.52-0.74；10 年，0.53-0.72）。大型校准为-0.13（95% PI：-1.62-1.37），校准斜率为0.90（95% PI：0.73-1.08）。 Predict-1B 10 年时的 AUC 为 0.59（95% PI：0.52-0.66）；校准稍低。 预防性对侧乳房切除术的决策曲线分析显示，对于 BRCA1/2 突变携带者和非携带者，PredictCBC-1A 在 4-10% 10 年 CBC 风险阈值之间具有潜在的临床效用。结论 我们开发了一个合理校准的模型来预测欧洲裔女性的 CBC 风险；然而，预测准确性中等。我们的模型显示了改进风险咨询的潜力，但有关对侧预防性乳房切除术的决策仍然具有挑战性，特别是在一般乳腺癌人群中，可获得的 BRCA1/2 突变状态信息有限。