NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England.
The Nightingale and Prevent Breast Cancer Centre, Manchester University NHS Foundation Trust, Manchester, M23 9LT, England.
Br J Cancer. 2023 Jun;128(11):2063-2071. doi: 10.1038/s41416-023-02250-w. Epub 2023 Apr 1.
Risk stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) could provide a better balance of benefits and harms. We developed BC-Predict, to offer women when invited to the NHSBSP, which collects standard risk factor information; mammographic density; and in a sub-sample, a Polygenic Risk Score (PRS).
Risk prediction was estimated primarily from self-reported questionnaires and mammographic density using the Tyrer-Cuzick risk model. Women eligible for NHSBSP were recruited. BC-Predict produced risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5-<8% 10-year) to have appointments to discuss prevention and additional screening.
Overall uptake of BC-Predict in screening attendees was 16.9% with 2472 consenting to the study; 76.8% of those received risk feedback within the 8-week timeframe. Recruitment was 63.2% with an onsite recruiter and paper questionnaire compared to <10% with BC-Predict only (P < 0.0001). Risk appointment attendance was highest for those at high risk (40.6%); 77.5% of those opted for preventive medication.
We have shown that a real-time offer of breast cancer risk information (including both mammographic density and PRS) is feasible and can be delivered in reasonable time, although uptake requires personal contact. Preventive medication uptake in women newly identified at high risk is high and could improve the cost-effectiveness of risk stratification.
Retrospectively registered with clinicaltrials.gov (NCT04359420).
作为国民保健制度（NHS）乳房筛查计划（NHSBSP）的常规部分进行风险分层，可以更好地平衡获益和危害。我们开发了 BC-Predict，在 NHSBSP 邀请女性时提供，该计划收集标准风险因素信息；乳房 X 光密度；以及在子样本中，多基因风险评分（PRS）。
风险预测主要是根据自我报告的问卷和乳房 X 光密度使用 Tyrer-Cuzick 风险模型进行估计。招募有资格参加 NHSBSP 的女性。BC-Predict 生成风险反馈信，邀请高危（≥8% 10 年）或中危（≥5-<8% 10 年）的女性预约讨论预防和额外筛查。
在参加筛查的女性中，BC-Predict 的总体参与率为 16.9%，有 2472 人同意参加研究；其中 76.8%的人在 8 周内收到风险反馈。与仅使用 BC-Predict 相比，现场招聘人员和纸质问卷的招聘率为 63.2%，而仅使用 BC-Predict 的招聘率<10%（P<0.0001）。高危女性的风险预约出勤率最高（40.6%）；其中 77.5%的人选择预防性药物。
我们已经证明，实时提供乳腺癌风险信息（包括乳房 X 光密度和 PRS）是可行的，并且可以在合理的时间内提供，尽管需要个人联系才能提高参与度。在新发现的高危女性中，预防性药物的使用率很高，这可能会提高风险分层的成本效益。
在 clinicaltrials.gov 上进行了回顾性注册（NCT04359420）。
