Noguchi Naomi, Teixeira-Pinto Armando, Marinovich Michael Luke, Louw Dominique Claire, Wylie Elizabeth Jane, Houssami Nehmat
Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW 2050, Australia.
The Daffodil Centre, University of Sydney (a Joint Venture with Cancer Council NSW), Camperdown, NSW 2050, Australia.
Cancers (Basel). 2025 Feb 26;17(5):810. doi: 10.3390/cancers17050810.
The aim of this study was to determine whether women at risk of having screen-detected (including detected at advanced stage) and interval breast cancer can be accurately identified using conventional risk factors collected by national screening programs.
All 1,026,137 mammography screening examinations for 323,082 women attending the BreastScreen Western Australia program (part of Australia's national biennial screening program) in July 2007-June 2017 contributed to models for predicting screen-detected breast cancers, screen-detected advanced cancers (≥pT2), and interval cancers.
In total, 7024 screen-detected (1551 in situ, 5472 invasive, of which 1329 were ≥pT2) and 1866 interval cancers (76 in situ, 1790 invasive) were diagnosed. In a multivariable model for screen-detected cancers, the ORs for the oldest age groups were 2.56 (CI 2.32-2.82) for 60-69 years and 3.60 (CI 3.23-4.00) for ≥70 years, and the OR for symptoms was 7.44 (CI 6.76-8.20). These associations were stronger for screen-detected advanced cancers. First-degree family history and a personal history of breast cancer were also associated with risk. In a multivariable model for interval cancers, the HR for dense breasts was 2.36 (CI 2.14-2.61) and the HR for symptoms was 3.27 (CI 2.53-4.24); family history and recent hormone replacement therapy use were also associated with risk. The areas under the receiver operating characteristic curves were 0.643 (CI 0.636-0.650) for screen-detected cancers, 0.651 (CI 0.638-0.664) for screen-detected advanced cancers, and 0.706 (CI 0.690-0.722) for interval cancers.
Older age and symptoms were the strongest predictors of overall and advanced screen-detected breast cancers. Dense breasts and symptoms were the strongest predictors of interval cancers. All models had moderate discrimination, approximating that for established models.
本研究旨在确定能否使用国家筛查项目收集的传统风险因素准确识别有筛查发现（包括晚期发现）和间期性乳腺癌风险的女性。
2007年7月至2017年6月期间，西澳大利亚乳腺癌筛查项目（澳大利亚全国两年一次筛查项目的一部分）对323,082名女性进行了1,026,137次乳房X线筛查检查，这些检查数据被用于建立预测筛查发现的乳腺癌、筛查发现的晚期癌症（≥pT2）和间期性癌症的模型。
总共诊断出7024例筛查发现的癌症（1551例原位癌，5472例浸润性癌，其中1329例≥pT2）和1866例间期性癌症（76例原位癌，1790例浸润性癌）。在筛查发现癌症的多变量模型中，60 - 69岁年龄组的比值比为2.56（95%置信区间2.32 - 2.82），≥70岁年龄组为3.60（95%置信区间3.23 - 4.00），有症状者的比值比为7.44（95%置信区间6.76 - 8.20）。这些关联在筛查发现的晚期癌症中更强。一级家族史和个人乳腺癌病史也与风险相关。在间期性癌症的多变量模型中，乳房致密的风险比为2.36（95%置信区间2.14 - 2.61），有症状者的风险比为3.27（95%置信区间2.53 - 4.24）；家族史和近期使用激素替代疗法也与风险相关。筛查发现癌症的受试者工作特征曲线下面积为0.643（95%置信区间0.636 - 0.650），筛查发现的晚期癌症为0.651（95%置信区间0.638 - 0.664），间期性癌症为0.706（95%置信区间0.690 - 0.722）。
年龄较大和有症状是筛查发现的总体乳腺癌和晚期乳腺癌的最强预测因素。乳房致密和有症状是间期性癌症的最强预测因素。所有模型的辨别能力中等，与既定模型相近。
