IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
Research Network on Health Services in Chronic Diseases (REDISSEC), Barcelona, Spain.
PLoS One. 2021 Mar 23;16(3):e0248930. doi: 10.1371/journal.pone.0248930. eCollection 2021.
Several studies have proposed personalized strategies based on women's individual breast cancer risk to improve the effectiveness of breast cancer screening. We designed and internally validated an individualized risk prediction model for women eligible for mammography screening.
Retrospective cohort study of 121,969 women aged 50 to 69 years, screened at the long-standing population-based screening program in Spain between 1995 and 2015 and followed up until 2017. We used partly conditional Cox proportional hazards regression to estimate the adjusted hazard ratios (aHR) and individual risks for age, family history of breast cancer, previous benign breast disease, and previous mammographic features. We internally validated our model with the expected-to-observed ratio and the area under the receiver operating characteristic curve.
During a mean follow-up of 7.5 years, 2,058 women were diagnosed with breast cancer. All three risk factors were strongly associated with breast cancer risk, with the highest risk being found among women with family history of breast cancer (aHR: 1.67), a proliferative benign breast disease (aHR: 3.02) and previous calcifications (aHR: 2.52). The model was well calibrated overall (expected-to-observed ratio ranging from 0.99 at 2 years to 1.02 at 20 years) but slightly overestimated the risk in women with proliferative benign breast disease. The area under the receiver operating characteristic curve ranged from 58.7% to 64.7%, depending of the time horizon selected.
We developed a risk prediction model to estimate the short- and long-term risk of breast cancer in women eligible for mammography screening using information routinely reported at screening participation. The model could help to guiding individualized screening strategies aimed at improving the risk-benefit balance of mammography screening programs.
多项研究提出了基于女性个体乳腺癌风险的个性化策略，以提高乳腺癌筛查的效果。我们设计并内部验证了一个适用于有资格接受乳房 X 线筛查的女性的个体化风险预测模型。
回顾性队列研究纳入了 121969 名年龄在 50 至 69 岁之间的女性，她们在西班牙的长期人群筛查计划中于 1995 年至 2015 年接受筛查，并随访至 2017 年。我们使用部分条件 Cox 比例风险回归来估计年龄、乳腺癌家族史、既往良性乳腺疾病和既往乳腺 X 线特征的调整后风险比（aHR）和个体风险。我们使用预期与观察比值和接收者操作特征曲线下面积对内模型进行了内部验证。
在平均 7.5 年的随访期间，2058 名女性被诊断患有乳腺癌。所有三个危险因素均与乳腺癌风险密切相关，乳腺癌家族史（aHR：1.67）、增生性良性乳腺疾病（aHR：3.02）和既往钙化（aHR：2.52）的女性风险最高。该模型总体上具有良好的校准能力（预期与观察比值在 2 年时为 0.99，在 20 年时为 1.02），但在患有增生性良性乳腺疾病的女性中略微高估了风险。接收者操作特征曲线下面积在 58.7%至 64.7%之间，具体取决于所选的时间范围。
我们开发了一个风险预测模型，用于使用常规报告的筛查参与信息来估计有资格接受乳房 X 线筛查的女性的短期和长期乳腺癌风险。该模型可以帮助指导个体化的筛查策略，旨在改善乳房 X 线筛查计划的风险效益平衡。
