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乳腺疾病监测联盟模型在乳腺不典型增生女性中的准确性。

Accuracy of the Breast Cancer Surveillance Consortium Model Among Women with LCIS.

机构信息

Weill Cornell Medical College, New York, NY, USA.

Breast Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, 300 East 66th Street, New York, NY, 10065, USA.

出版信息

Breast Cancer Res Treat. 2022 Jul;194(2):257-264. doi: 10.1007/s10549-021-06499-8. Epub 2022 May 20.

Abstract

PURPOSE

The Breast Cancer Surveillance Consortium (BCSC) model predicts risk of invasive breast cancer risk based on age, race, family history, breast density, and history of benign breast disease, including lobular carcinoma in situ (LCIS). However, validation studies for this model included few women with LCIS. We sought to evaluate the accuracy of the BCSC model among this cohort.

METHODS

Women with LCIS diagnosed between 1983 and 2017 were identified from a prospectively maintained database. The BCSC score was calculated; those with prior breast cancer, unknown breast density, age < 35 years or > 74 years, or with history of chemoprevention use were excluded. The Kaplan-Meier method was used to estimate incidence rates. Time-dependent receiver operating characteristic (ROC) analysis was used to analyze the discriminative capacity of the model.

RESULTS

1302 women with LCIS were included. At a median follow-up of 7 years, 152 women (12%) developed invasive cancer (6 with bilateral disease). Cumulative incidences of invasive breast cancer were 7.1% (95% CI 5.6-8.7) and 13.3% (95% CI 10.9-15.6), respectively, and the median BCSC risk scores were 4.9 and 10.4, respectively, at 5 and 10 years. The median 10-year BCSC score was significantly lower than the 10-year Tyrer-Cuzick score (10.4 vs 20.8, p < 0.001). The ROC curve scores (AUC) for BCSC at 5 and 10 years were 0.59 (95% CI 0.52-0.66) and 0.58 (95% CI 0.52-0.64), respectively.

CONCLUSION

The BCSC model has moderate accuracy in predicting invasive breast cancer risk among women with LCIS with fair discrimination for risk prediction between individuals.

摘要

目的

乳腺癌监测联合会(BCSC)模型基于年龄、种族、家族史、乳房密度和良性乳腺疾病史(包括小叶原位癌[LCIS])预测浸润性乳腺癌风险。然而,该模型的验证研究包括的 LCIS 患者较少。我们旨在评估该模型在这一人群中的准确性。

方法

从一个前瞻性维护的数据库中确定了 1983 年至 2017 年期间诊断为 LCIS 的女性。计算了 BCSC 评分;排除了患有先前乳腺癌、未知乳房密度、年龄<35 岁或>74 岁或使用化学预防的女性。使用 Kaplan-Meier 方法估计发病率。使用时间依赖性接受者操作特征(ROC)分析来分析模型的区分能力。

结果

纳入了 1302 例 LCIS 患者。中位随访 7 年后,152 例(12%)发生浸润性癌(6 例双侧疾病)。浸润性乳腺癌的累积发生率分别为 7.1%(95%CI 5.6-8.7)和 13.3%(95%CI 10.9-15.6),分别在 5 年和 10 年时的 BCSC 风险评分中位数分别为 4.9 和 10.4。中位 10 年 BCSC 评分显著低于 10 年 Tyrer-Cuzick 评分(10.4 比 20.8,p<0.001)。BCSC 在 5 年和 10 年时的 ROC 曲线评分(AUC)分别为 0.59(95%CI 0.52-0.66)和 0.58(95%CI 0.52-0.64)。

结论

BCSC 模型在预测 LCIS 患者的浸润性乳腺癌风险方面具有中等准确性,在个体之间的风险预测方面具有良好的区分能力。

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